The Data Engineer List

Live index

The best data engineer jobs, ranked.

Data engineering pay has split in two: companies with a dedicated data engineer ladder post mid-level bands between roughly $130k and $225k, Netflix posts $380k–$610k in cash, and the platform companies hire data engineers as senior software engineers. This is the living index of the data orgs worth your application — posted pay, which companies actually use the title, and whether they hire remote or entry-level, re-verified as the market moves. Every number traces to a posted range, a live careers page, or levels.fyi.

Programs ranked

Hiring now

Remote friendly

$610k

Top core-req base

Sources: posted salary ranges, levels.fyi, and company careers pages. Last verified October 10, 2026. How we rank →

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Tier 1The destinations — dedicated data engineering ladders, top-of-market pay, and the platforms the rest of the industry runs on

Meta data engineers design logging, data models and ETL pipelines that feed analytics for Facebook, Instagram, WhatsApp, Threads and Reality Labs, working with software engineers, data scientists and PMs. Product Analytics reqs dominate, with 2026 growth in AI-facing reqs (Ranking/AI, Meta Superintelligence Labs). It is the largest dedicated, leveled DE ladder on this list, with an intern path and a posted 2+ year tier.

Base salary

$147k–$208k

Locations

Menlo Park · Seattle · NYC · SF · Chicago · DC

Work setup

Hybrid, about 3 days a week in office company-wide (Instagram requires 5 days from February 2, 2026); two senior and staff data engineer reqs list ‘Remote, US’

Experience

Mid-level req: bachelor’s or equivalent, 4+ years in data-focused roles (analyst, data scientist, data engineer), 4+ years of SQL, ETL, data modeling and one language (Python, C++, C#, Scala). Senior reqs need 7+ years and staff reqs 10–12+ years of data-warehouse and custom-ETL experience. Entry level exists: a 2+ year Data Engineer, Product Analytics req ($114K–$173K) and the intern program. Recent reqs prefer demonstrated AI-tool use in data workflows.

Worth knowing: After announcing about 8,000 layoffs (10%) and about 6,000 unfilled reqs on May 19, 2026, Meta still posted new data engineer reqs through September 2026 — including two for Meta Superintelligence Labs (posted Sep 9 and Sep 14, 2026).

10 US full-time ‘Data Engineer’ reqs open in Meta’s Data Engineering sub-team as of Oct 10, 2026 — three Product Analytics reqs at 2+, 4+ and 7+ years, Teen & Family Experience, Analytics (Ranking, AI), two for Meta Superintelligence Labs and three Technical Leadership reqs at 10–12+ years — plus a Summer 2027 Data Engineer Intern; offices include Menlo Park, Sunnyvale, Burlingame, San Francisco, Fremont, Bellevue, Redmond, Seattle, New York, Chicago and Washington DC, with Remote US on two reqs

Prep with Aced View open roles

Salary band, hiring status & score breakdown — see the full Meta Data Engineer page →Meta interview guide →

Netflix data engineers build batch and real-time pipelines and data models that power analytics, product features and ML across Growth, Finance, Content and Studio. 2026 hiring concentrates on Ads data engineering (inventory, targeting, identity, measurement) plus analytics engineers embedded with data science. It is a senior-heavy, high-autonomy org with no junior ladder for data engineers.

Base salary

$380k–$610k

Locations

US remote (hubs in Los Gatos and LA)

Work setup

Remote-eligible — the L5 Data Engineer posting accepts fully remote US candidates (with occasional Los Gatos visits) or relocation to Los Gatos; the careers system tags both L6 Ads reqs ‘onsite’ despite a ‘Remote, United States’ location, so confirm per req

Experience

Senior-only bar. The L5 Data Engineer req wants proficiency in Java, Scala or Python plus SQL, deep strength in distributed data processing, data-service engineering or data modeling, and Spark or Flink at web scale; Ads reqs add batch and streaming pipelines on Spark/Flink/Hive/Hadoop and warehouse modeling. L6/Staff reqs state 12+ and 15+ years. No entry-level DE path.

Worth knowing: Netflix pays data engineers entirely in cash with no bonuses (‘compensation structure consists solely of an annual salary’): L5 posts $380K–$610K and the Staff (L6) Ads Data Engineer req posts $510K–$820K.

About 19 data-centric US reqs as of Oct 10, 2026: four ‘Data Engineer’-titled reqs (two L5 including one for Ads, two L6/Staff Ads), nine ‘Analytics Engineer 5’ reqs and roughly six data-platform and data-products SWE reqs, mostly in the Data & Insights org and heavy on Ads data, all listed ‘Remote, United States’

Prep with Aced View open roles

Salary band, hiring status & score breakdown — see the full Netflix Data Engineer page →Netflix interview guide →

Amazon data engineers build and run ETL pipelines, warehouses and data lakes — largely Redshift, EMR, S3, Glue and Kinesis on AWS — that feed finance, operations, advertising and AWS business analytics. Most reqs are embedded in a line of business such as WW Ops Finance, AWS Marketplace or Ring, so the day-to-day varies by team. With 65 open reqs it has the most data engineering openings on this list, a clearly leveled DE ladder, and a dedicated DE internship.

Base salary

$132k–$179k

Locations

Seattle · Bellevue · Austin · LA area · NYC · Northern Virginia · Dallas

Work setup

In office 5 days a week — every DE req location is tagged on-site, and Amazon’s corporate five-day policy has applied since January 2025

Experience

DE II and plain ‘Data Engineer’ reqs usually ask for 3+ years of data engineering (some AWS Analytics Engineering and BI reqs ask for 5+), plus data modeling, warehousing and ETL, SQL and a scripting language such as Python; Senior and DE III reqs ask for 5–7+ years. A DE I req (Zappos Analytics) asks for a bachelor’s plus 1+ years, and the 2027 internship is the entry path. Posted stacks lean on Redshift, EMR, S3, Glue, Kinesis and Lambda.

Worth knowing: Amazon cut roughly 30,000 corporate jobs between October 2025 and January 2026, yet its careers feed still shows 65 US Data Engineering reqs, many posted in the past two weeks — and all of them are on-site.

65 US reqs in the Data Engineering job family on amazon.jobs as of Oct 10, 2026 — about 20 titled DE II, four DE III, four Senior, four managers, a Principal, a DE I, an intern req and 30 plain ‘Data Engineer’ reqs, posted through Oct 9 — across AWS (15), Finance and WW Ops Finance (14), Alexa, Devices and Ring (8), transportation and logistics (5), Ads, Prime Video and Studios, Amazon Leo, Whole Foods and Zappos; Seattle and Bellevue hold 35 of the 65, with Austin, Southern California, New York, Northern Virginia and Dallas next (a floor, because the search feed is relevance-limited)

Prep with Aced View open roles

Salary band, hiring status & score breakdown — see the full Amazon Data Engineer page →Amazon interview guide →

Tier 2The strong seats — big data orgs and data-platform builders with real scale and pay to match

Airbnb data engineers and analytics engineers build Airflow-orchestrated pipelines, dimensional models and Minerva metric definitions that feed finance, infrastructure and product decisions, and a growing share of the work measures AI cost and usage. Open reqs are Senior Staff or Staff level, remote-eligible across the US, and increasingly blend DE and AE responsibilities within one team. Data-platform seats are Staff SWE reqs on the engineering ladder.

Base salary

$179k–$210k

Locations

US remote (approved states only)

Work setup

Remote — every open data req is US-remote-eligible, with occasional office visits or offsites agreed with your manager; you must live in a state where Airbnb has a registered entity

Experience

Senior Analytics Engineer: 5+ years in analytics or data engineering, SQL, Python, Spark/Presto/Hive and dimensional modeling. Senior Staff Data Engineer: 12+ years (BS/MS) or 9+ (PhD). Staff SWE Data Warehouse: 10+ years in data infrastructure (Spark, Presto/Trino, Java/Scala). No entry-level data engineer req is open.

Worth knowing: Apache Airflow was started at Airbnb in October 2014 and became an Apache Top-Level Project in January 2019 — and the current Senior Staff Data Engineer req still describes Airflow-orchestrated pipelines and Minerva metric definitions.

Four core US data reqs open on a 161-req global board as of Oct 10, 2026 — Senior Staff Data Engineer (Foundational Data), Senior Analytics Engineer (Airbnb.org), Staff SWE Data Warehouse and Staff SWE Data Authoring — plus a data-focused Staff backend role in Marketplaces & Intelligence; all are US-remote-eligible, and a Unified Data Store Staff SWE req is Brazil-only

Prep with Aced View open roles

Salary band, hiring status & score breakdown — see the full Airbnb Data Engineer page →Airbnb interview guide →

Databricks sells the data-engineering stack (Spark, Delta, Lakeflow Pipelines), so its US data-platform seats are product engineers building the runtime, storage and pipeline services rather than internal ETL builders. Reqs skew Senior and Staff, JVM/C++ and distributed-systems heavy, in SF, Mountain View, Bellevue and NYC. Customer-facing data-engineering roles (Specialist Solutions Architect, Forward Deployed Engineer) are tracked on The FDE List instead.

Base salary

$166k–$225k

Locations

SF · Mountain View · Bellevue · NYC

Work setup

Hub-based — data-platform reqs list only SF, Mountain View, Bellevue and NYC seats and none are tagged remote

Experience

Core reqs are Senior and Staff+: Senior SWE Distributed Data Systems asks for a BS in CS or equivalent, 5+ years of production Java, Scala or C++, and distributed-systems, database or Spark experience; Senior Staff Lakeflow Pipelines asks for 10+ years. No entry-level or new-grad data engineer path is posted.

Worth knowing: On February 9, 2026 Databricks reported a revenue run-rate above $5.4B (up 65% year over year) with positive trailing-12-month free cash flow — yet its public board has no US req titled Data Engineer.

No US req titled Data Engineer as of Oct 10, 2026, but about 12 US product-engineering reqs carry a data-platform or pipelines scope — six Senior and Staff Distributed Data Systems reqs, two Lakeflow Pipelines Staff+ reqs, a Senior Engineering Manager for the Pipelines Engine, a Unity Catalog Data Governance req and two NYC data-product Staff SWE reqs — across San Francisco, Mountain View, Bellevue and New York; the ‘Software Engineer – Data Platform’ titles are Bengaluru-only

Prep with Aced View open roles

Salary band, hiring status & score breakdown — see the full Databricks Data Engineer page →

Interviewing for data engineer roles?Aced’s Data Engineering interview course covers SQL, data modeling, pipeline and system design, and the behavioral rounds.

Start prepping →

Apple data engineers build pipelines, models and data products behind services (iCloud, Music, Retail, Finance, Health) and Apple’s internal AI/ML and data platforms. Most hiring is senior (4–5+ years), with posted stacks such as Spark, Kafka, Flink, Iceberg and Kubernetes on platform teams and Snowflake or Databricks on analytics teams. Data engineering is folded into software engineering rather than being its own ladder, and nearly every seat is hybrid in California, Austin or Seattle.

Base salary

$129k–$225k

Locations

Cupertino · Sunnyvale · Austin · Seattle

Work setup

Hybrid, about 3 days in office (Apple’s long-standing Monday, Tuesday and Thursday pattern); postings show no home-office option

Experience

Typical minimums on DE reqs: 3+ years (Capacity Planning), 4+ years (AIML Data Engineer), 5+ years (Finance Data Engineer and Senior DE) and 10+ years for Senior Data Engineer, AIML — strong SQL and Python, with Scala, Java and Spark on senior reqs and Snowflake or Databricks on some, and usually a bachelor’s in CS or a related field. No entry-level DE req is open; early career comes via the internship or IS&T early-career SWE reqs.

Worth knowing: Apple’s 2026 DE reqs skew toward AI — titles include ‘AIML Data Engineer’, ‘Data Engineer (Agentic AI, LLM Training)’ and ‘Simulation Generative Data Engineer’ — and about 31 IC reqs sit in the AiDP and Apple Data Platform orgs.

About 19 US individual-contributor reqs titled Data Engineer or Analytics Engineer on jobs.apple.com as of Oct 10, 2026 (ten posted since July 2026), plus about 31 IC software-engineer reqs in the AI & Data Platforms and Apple Data Platform orgs, mostly in Sunnyvale and Austin; teams include Apple Data Platform, AiDP (IS&T), AIML, Finance, iCloud Insights, Retail Data Products, Health and Apple Services Engineering analytics

Prep with Aced View open roles

Salary band, hiring status & score breakdown — see the full Apple Data Engineer page →Apple interview guide →

Google data engineers build and own data products, pipelines and data-quality frameworks for specific product areas (Merchant Shopping, gTech users and products, Google.org) rather than a central DE org. Most similar work sits under Software Engineer titles, so ‘Data Engineer’ reqs are few and tend to require 3–5+ years. Pay is posted as base plus a 15% bonus target and equity.

Base salary

$130k–$187k

Locations

Mountain View · Seattle · Kirkland · Boulder · SF

Work setup

Hybrid — most Googlers work in office about 3 days a week, remote by exception; no remote-eligible data engineer req, and in-person interviews are usually required

Experience

Data Engineer: bachelor’s or equivalent plus 3 years with data-processing software (Hadoop, Spark, Pig, Hive; MapReduce, Flume), production pipelines with multiple upstream sources, automated pipeline tests, and Java, C++, Python, Go or JavaScript. Senior: 5 years designing pipelines and dimensional modeling (Flume internally; Dataflow or Spark externally) and 5 years coding. No entry-level data engineer req is open.

Worth knowing: Google has only three ‘Data Engineer’ reqs open in the US, all posted September 28–30, 2026 — and the Merchant Shopping req asks for a ‘full-stack’ engineer who bridges software, data engineering and data science using genAI.

Only three US reqs carry ‘Data Engineer’ in the title as of Oct 10, 2026, all posted September 28–30: Data Engineer, Merchant Shopping (Mountain View); Senior Data Engineer, gTech Users and Products (Boulder); Senior Data Engineer, Google.org for Social Impact (Mountain View, San Francisco, Seattle, Kirkland). Most Google data-pipeline work is posted under Software Engineer titles (BigQuery, storage analytics, AI data quality).

Prep with Aced View open roles

Salary band, hiring status & score breakdown — see the full Google Data Engineer page →Google interview guide →

Tier 3The specialists and SWE-ladder shops — strong seats where data engineering is a smaller team or is hired as software engineering

Atlassian data engineers own end-to-end ELT/ETL pipelines, data models, quality frameworks and on-call for product, growth and go-to-market data, partnering with data science and product engineering. Postings stress Spark, Airflow and Databricks, metrics definition, logging instrumentation and data governance. The org is distributed-first, has a rare dedicated graduate DE program, and is adding AI-oriented data work such as an ‘AI context layer’ for agents.

Base salary

$139k–$219k

Locations

Six US hubs + Americas remote (Seattle for grads)

Work setup

Distributed-first — Atlassians choose to work in an office, from home or a mix; the senior DE req lists Remote Americas, while the graduate and intern roles require the Seattle hub

Experience

Senior Data Engineer: BE or CS or equivalent plus 6+ years as a data engineer; Spark pipelines with Airflow or similar, Databricks and APIs, Redshift/DynamoDB/Mongo/Postgres and data lakes, Python or Scala, strong SQL, CI/CD. Graduate DE: BS or MS in CS graduating by August 2027, Python, SQL, data structures and demonstrated DE interest. Neither early-career role is open to F-1/J-1 students or sponsorship.

Worth knowing: Atlassian cut about 1,600 jobs (about 10%) on March 11, 2026, with 900+ in software R&D — and is still posting a dedicated 2027 Graduate Data Engineer role, a DE intern role and new senior DE roles on the acquired DX team.

About seven US-eligible data-engineering reqs open as of Oct 10, 2026: Senior Data Engineer (Americas remote, Austin, Mountain View, NYC, Seattle, DC, SF), Senior Data Engineer for DX (Salt Lake City or remote), Data Engineer 2027 Graduate (Seattle), Data Engineer Intern 2027 (Seattle), a Principal Analytics Engineering analyst, a Senior Principal SWE for the Trusted Data Platform and a Senior EM for the same; larger DE reqs (Principal Data Engineer, Senior DE Manager) are posted in India

Prep with Aced View open roles

Salary band, hiring status & score breakdown — see the full Atlassian Data Engineer page →Atlassian interview guide →

Stripe data engineering is infrastructure engineering: building batch orchestration (Airflow, Spark, Iceberg), streaming and incremental transformation (Flink, Kafka), and serving layers (Trino, Pinot) that power payments, the ledger, fraud (Radar), reporting (Sigma) and financial reconciliation. There is no separate ‘Data Engineer’ title; candidates apply as backend or infrastructure software engineers and are team-matched. Pay is posted in the high-$200Ks for senior US roles.

Base salary

$206k–$286k

Locations

Seattle · SF · NYC · Chicago · US remote

Work setup

Hybrid — office-assigned Stripes spend at least 50% of the month in their local office, and the Seattle req lists ‘50% telecommuting permitted’; the Data Transformation and Core Technology reqs list US remote

Experience

Seattle senior data-pipeline req: bachelor’s plus 5 years of software engineering (Java, Scala or Python), 4 years of complex SQL and large-scale pipelines, 4 years in fintech and 1 year of Apache Spark. The Core Technology infra req asks for 2–12+ years in Go, Java or C++. The new-grad path is generalist SWE (at most 18 months of experience).

Worth knowing: Stripe’s Data Transformation org says its top priority is delivering high-quality materialized datasets for Stripe products and AI agents (EM req posted Apr 13, 2026) — yet the IC data-platform reqs on its board are in Bengaluru, Dublin and Toronto, with almost no US data-pipeline ICs open.

Thin in the US as of Oct 10, 2026: about three reqs with a data-pipeline or data-infrastructure scope among 729 Stripe postings — Senior SWE Backend (Seattle, financial data pipelines), Engineering Manager Data Transformation (Seattle, SF, NYC or US remote) and Backend Engineer Core Technology (US remote, Chicago, Seattle or SF, covering Trino and Pinot data infrastructure); the IC data-platform reqs are in Bengaluru, Dublin and Toronto

Prep with Aced View open roles

Salary band, hiring status & score breakdown — see the full Stripe Data Engineer page →

DoorDash data engineers build and operate the batch and streaming pipelines, lake and warehouse models and platform tooling behind reporting, product analytics, marketing optimization, financial reporting and real-time personalization. Hiring is concentrated in two groups: Data Engineering (Python, Airflow, Spark, Kafka/Flink, data modeling) and Core Data Platform (ingestion frameworks, the Spark platform, the lakehouse, governance). The titles are software-engineering titles on the I-ladder rather than ‘Data Engineer’.

Base salary

$131k–$192k

Locations

SF · Sunnyvale · Seattle · NYC

Work setup

Hybrid — the Senior DE posting says ‘This is a hybrid position’ in Sunnyvale, SF or Seattle, and the Data Platform req requires living in or relocating to the Bay Area, Seattle or NYC; only the security data req is remote

Experience

SWE II (I4): 3+ years in data engineering or BI, Python or Java, 3+ years of ETL orchestration (Airflow, Flink, Oozie or Azkaban on AWS or GCP), Spark/Hive/Druid/Presto, Kafka/Flink, strong SQL. Senior (I5) asks for 5+ years and Staff for 8+. The 2026 reqs ask for proficiency with AI coding tools (Claude Code, Codex, Cursor). No data-engineer-specific entry-level path; the generalist SWE I req asks for two internships and at most two years of experience.

Worth knowing: DoorDash’s 2026 data reqs list proficiency with AI coding tools (Claude Code, Codex, Cursor) as a requirement, and in March 2026 its careers blog announced it is replacing traditional coding rounds with a 60-minute AI-assisted engineering working session.

About 10 data-focused US reqs on DoorDash’s US Greenhouse board (464 reqs total) as of Oct 10, 2026: SWE II, Senior and Staff Data Engineering, SWE Data Platform (All Teams), SWE Data and AI Platform, Spark Platform (Senior SWE and SWE), Staff SWE Event Streaming Systems, an Engineering Manager for Data, and a Senior Security Data Engineer (US remote); offices are San Francisco, Sunnyvale, Seattle and New York

Prep with Aced View open roles

Salary band, hiring status & score breakdown — see the full DoorDash Data Engineer page →DoorDash interview guide →

Microsoft data engineers build and operate data platforms and pipelines for product telemetry, marketing, ads and finance, increasingly on Fabric, OneLake, Databricks/Spark and Azure Data Factory. Open DE-titled reqs are Senior and above and sit in AdTech and Global Marketing data teams. Mid-level data engineering work is typically posted as Software Engineer II, so a search on ‘data engineer’ alone understates the real demand.

Base salary

$120k–$235k

Locations

Redmond · NYC · Atlanta · Mountain View

Work setup

Hybrid, 3 days a week in office — all three DE reqs carry the ‘3 days / week in-office’ field, under the policy that began with Puget Sound staff in February 2026

Experience

Senior Data Engineer (IC4): bachelor’s plus 4+ years (or master’s plus 3+) in business analytics, data science, software development, data modeling or data engineering. Principal Data Engineer: 8+ years plus Spark, Python, SQL and Delta Lake or Parquet. SWE II data-team reqs ask for a bachelor’s plus 2+ years of coding. Preferred stack: Azure, Microsoft Fabric, Databricks, Spark, Azure Data Factory, Synapse and Event Hubs. No entry-level DE req is open.

Worth knowing: Only 3 of roughly 1,220 US openings on Microsoft’s careers site carry a ‘Data Engineer’ title as of October 10, 2026 — in the middle of a very large AI and data-platform build-out — because much of the data engineering is posted as Software Engineer II or Senior SWE.

Thin: three US reqs carry a ‘Data Engineer’ title among about 1,220 US openings on Microsoft’s careers site as of Oct 10, 2026 — Senior Data Engineer, AdTech Clean Room (Redmond, New York, Atlanta, Mountain View; posted Oct 6), Senior Data Engineer, Global Marketing Data Engineering (Redmond; posted Oct 3) and Principal Data Engineer (Redmond; posted Sep 30) — with other data-platform work posted as Software Engineer II or Senior SWE reqs, such as a SWE II on Global Marketing Data Engineering built on Fabric and OneLake

Prep with Aced View open roles

Salary band, hiring status & score breakdown — see the full Microsoft Data Engineer page →Microsoft interview guide →

Uber’s data engineers work as software engineers on the lake and streaming stack (Hudi, Spark, Flink, Presto) and on pipelines for domain teams like AV Labs, capacity planning and finance. Open reqs are mostly SWE II to Senior, with Python, Spark, Flink and table-format skills. The September 2026 restructuring merged engineering and science divisions and shifted investment toward robotaxis, so the org is in flux.

Base salary

$171k–$190k

Locations

Sunnyvale · SF · NYC

Work setup

In office 3 days a week since June 2025; after the September 2026 restructuring, remote roles are ending with under 1% of staff allowed to work remotely

Experience

SWE II Data Infrastructure: BS in CS, 3+ years building data infrastructure or distributed backend systems, Python, C++ or Go, Spark/Flink/Ray, and Parquet, Iceberg or Delta table formats. Senior SWE (Data & Backend): 6+ years in backend or data engineering with advanced SQL and data warehousing. No data-engineer-specific entry-level req is open.

Worth knowing: Hudi was designed and built at Uber; its January 16, 2026 engineering post reports about 19,500 Hudi datasets, about 6 trillion rows ingested per day and about 350 logical PB stored.

About 4 of 319 US reqs (622 global) carry a data-platform or pipeline scope as of Oct 10, 2026 — SWE II Data Infrastructure for AV Labs (Sunnyvale), Senior SWE Data & Backend (Sunnyvale), SWE II Capacity & Efficiency Engineering (San Francisco, planning data pipelines) and Application Developer II Finance Data Platform (San Francisco), plus a Data Trust & AI Governance Lead in NYC — following the September 2, 2026 announcement of about 3,300 job cuts

Prep with Aced View open roles

Salary band, hiring status & score breakdown — see the full Uber Data Engineer page →Uber interview guide →

The comp landscape

Posted base-salary bands for each program’s core data engineering req, US market — equity and bonus come on top. Where a company posts no “Data Engineer” title (Databricks, Uber, Stripe), the band is the closest data-platform engineering req, usually a senior one. Full breakdown in the Data Engineer salary guide.

Netflix

$380k–$610k

Stripe

$206k–$286k

Microsoft

$120k–$235k

Apple

$129k–$225k

Databricks

$166k–$225k

Atlassian

$139k–$219k

Airbnb

$179k–$210k

What does a data engineer do?

A data engineer builds the pipelines, models and platforms that turn raw events into data a company can use: ingesting and transforming data (batch with Spark and Airflow, streaming with Kafka and Flink), designing warehouse and lakehouse models, defining metrics, and keeping it all reliable and cheap at scale. Unlike a data analyst or data scientist, the job is software engineering with data as the product — you ship pipelines and tooling, not dashboards.

The title means different things at different companies. Meta, Netflix, Atlassian, Airbnb and Google run a dedicated Data Engineer title and ladder; Databricks, Uber and Stripe hire the same work as software engineers on data-platform teams. The interview loop is consistent either way: SQL (often live), a Python or coding round, dimensional data modeling, pipeline or system design, and behavioral.

Preparing for the loop? Start with our guides to the Meta data engineer interview, Amazon data engineer interview, and Netflix data engineer interview.

How we rank

Every program gets an Index score out of 100, built from four weighted dimensions. Scores are editorial judgments grounded in the data below — not paid placements.

30%

Compensation

Posted data engineer salary bands, levels.fyi data, and verified offer reports — total comp where a data-engineer-specific sample exists, base bands otherwise.

25%

Program maturity

How real the data org is: a dedicated data engineer title and ladder, named teams, the platforms it built, and whether there is an intern or new-grad path.

25%

Career capital

What the role does for the rest of your career — brand strength, the scale and variety of data you work on, and the tooling you learn (Spark, Airflow, Flink, Iceberg, Hudi, Presto).

20%

Momentum

Open req counts, remote and entry-level paths, and whether the data org is expanding, holding, or working through a restructuring.

We also track Snowflake, Spotify, LinkedIn, Capital One, Shopify, Robinhood, Pinterest and Block, currently outside the ranking and queued for the next data pass. Databricks, Uber and Stripe stay ranked despite posting no ‘Data Engineer’ title because their data-platform teams do the same work under software engineering titles; where that leaves only a senior posted band, the compNote says so. Total compensation is shown only where levels.fyi has a data-engineer-specific sample, which is why Databricks, Uber, Stripe, Atlassian and Apple show base bands alone.

Compensation data comes from posted salary ranges (required in several US states), levels.fyi, and public offer reports; figures are US-market and vary by level and location. Hiring status reflects each company’s careers page as of October 10, 2026. Spotted something outdated? Email [email protected].

Frequently asked questions

Posted mid-level base bands at the companies with a data engineer title run from about $130k to $225k: Google $130,000–$187,000 (plus a 15% bonus target), Amazon Data Engineer II $132,100–$178,800 (New York $160,113–$196,600), DoorDash I4 $130,600–$192,000, Meta $147,000–$208,000, Uber SWE II $171,000–$190,000 and Apple’s ICT-spanning $129,300–$225,300. Senior bands run higher — Atlassian $138,942–$218,550, Airbnb $179,000–$210,000, Microsoft IC4 $119,800–$234,700, Databricks $166,000–$225,000 and Stripe $206,086–$285,600 — and Netflix posts $380,000–$610,000 in cash for an L5. With equity, levels.fyi puts total compensation at $173k–$225k at Amazon L5, $208k–$238k at Microsoft, $236k–$415k at Meta, $244k–$307k at Google, $308k–$385k at DoorDash, $408k–$523k at Airbnb (senior-heavy) and $515k–$650k at Netflix.

Netflix, by a wide margin on posted numbers: $380,000–$610,000 for an L5 data engineer and $510,000–$820,000 for the Staff Ads data engineer reqs, paid entirely as salary with no bonus. Below that, Stripe posts the highest base ($206,086–$285,600, a senior backend req on its financial data platforms), and on reported total compensation Airbnb ($408k–$523k, mostly senior) and DoorDash ($308k–$385k) lead the companies that hire at mid level, followed by Meta ($236k–$415k across E3–E5).

Five rounds in roughly the same shape everywhere: a recruiter screen, a technical screen that is mostly live SQL, then an onsite of four to six rounds covering SQL, Python or ETL coding, dimensional data modeling, pipeline or system design and behavioral. Meta’s screen splits 25 minutes of SQL and 25 of coding before three 60-minute ‘Full Stack’ rounds on one case study; Amazon asks for facts, dimensions and slowly changing dimensions, puts a Leadership Principle question in every round and ends with a Bar Raiser; Airbnb runs five to seven rounds including business acumen and core values; Google adds a hiring committee and takes six to twelve weeks; and DoorDash says it has replaced algorithmic coding with a 60-minute AI-assisted working session in your own IDE since March 2026.

Meta (a dedicated E3–E7 ladder with 10 open US reqs), Netflix (Data Engineer L3–L8 inside Data & Insights), Amazon (a Data Engineering job family from DE I to Principal with 65 open reqs), Atlassian (an Analytics & Data Science job family with its own graduate program), Airbnb (Data Engineer and Analytics Engineer titles on the engineering ladder), Google (three titled reqs; most pipeline work sits under Software Engineer), Apple (ICT2–ICT5 within the software family) and Microsoft (a Data Engineering discipline, with three titled reqs open). Databricks, Uber and Stripe post none — their data-platform work is hired as software engineering — and DoorDash uses ‘Software Engineer, Data Engineering’ on its I-ladder.

Spark appears on nearly every posting on this list, and Airflow on most of the pipeline-building ones (Airbnb, where it was created; DoorDash; Atlassian; Stripe). Beyond that the stack follows the company: Kafka and Flink for streaming at DoorDash, Uber, Stripe and Apple; table formats such as Iceberg (Netflix, Uber, Stripe), Hudi (Uber) and Delta Lake (Databricks, Microsoft); Redshift, EMR, Glue and Kinesis at Amazon; BigQuery, Dataflow and Flume at Google; Fabric, OneLake and Synapse at Microsoft; Presto and Trino at Meta, Airbnb and Stripe. Every loop tests SQL and data modeling first — the tools come second.

Three of the twelve have a real path. Atlassian posts a dedicated ‘Data Engineer, 2027 Graduate U.S.’ req (Seattle, graduating by August 2027, $124,200–$162,150 in its top pay zone) plus a 2027 summer DE internship; Meta posts a 2+ year Data Engineer, Product Analytics tier at $114,000–$173,000 and a Summer 2027 Data Engineer Intern req; Amazon has a DE I rung (bachelor’s plus 1+ years) and a 2027 DE internship with Winter, Summer and Fall starts. Apple’s Applied Data Solutions internship and DoorDash’s generalist SWE I req are adjacent routes. Google, Netflix, Airbnb, Databricks, Uber, Stripe and Microsoft have no entry-level data engineer req open.

At about half the companies here. Netflix lists every open data req as ‘Remote, United States’, Airbnb’s four open data reqs are all US-remote-eligible, Atlassian’s senior DE req is Remote Americas, Stripe’s Data Transformation and Core Technology reqs list US remote, and Meta tags two senior and staff DE reqs ‘Remote, US’. Amazon is five days in office on every DE req, Uber is three days with remote roles ending after its September 2026 restructuring, and Apple, Google and Microsoft are hybrid at about three days a week; Databricks hires into its SF, Mountain View, Bellevue and New York hubs.

It depends on the company more than the market. Amazon shows 65 open US data engineering reqs after cutting roughly 30,000 corporate jobs, Meta posted new DE reqs through September after its May layoffs (including two for Meta Superintelligence Labs), Netflix has about 19 data-centric reqs with an Ads push, and Apple lists about 19 titled DE reqs plus 31 data-platform SWE reqs. On the other side, Microsoft has three titled DE reqs among 1,220 US openings, Google three, Stripe about three US data-infra reqs, and Uber about four after 3,300 job cuts. The clearest 2026 shift is toward AI: AI-training, agent and ads-measurement data work shows up at Meta, Apple, Netflix and Atlassian, and DoorDash now requires proficiency with AI coding tools.

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