Role Description We are seeking an experienced Lead Data Engineer with strong Terraform expertise to design, build and maintain scalable data solutions on Google Cloud Platform. In this role, you will lead the developmen…
Engineering & IT · Remote
Remote Data Engineer jobs
Data engineers build the pipelines and warehouses that move data from source systems to the people and models that need it, keeping it fresh, correct, and queryable at scale.
21,917
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$38–$94/hr
Typical pay range
$129k
Median, full-time
9
Fresh in this list
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01
Open data engineer roles
12 shown of 21,917 · sorted by freshness
Role Description As a Senior Data Engineer, you will design, build, and support the core systems that power our data platform to enable fast, data-driven decisions. You will create scalable data pipelines, self-service t…
$175k - $180k
analysts, and IT teams to gather requirements and deliver scalable data solutions that support strategic business initiatives. ~... ...Serve as a technical expert and mentor to team members on data engineering best pract…
$170k - $190k
Role Description As a Lead Data Engineer, you will serve as a senior technical leader within the Data Engineering organization, helping define the architecture, engineering standards, and best practices that support Walk…
Role Description 弊社のトップクライアントであるLINEヤフーグループ企業にて、月間3,000万人以上が利用する大規模サービスのデータ基盤構築をリードする Data Engineerを 募集しています。独自の検証データや大規模なユーザー行動データを活用し、データドリブンな意思決定、AI活用、プロダクト成長を支える重要なポジションです。 本ポジションでは、同社が保有する独自の「検証データ」と月間3,000万人以上のユーザー…
$195k
Role Description We are looking for a Senior Data Engineer to join our lean, high-impact Data & Analytics team (currently a data analyst and a data engineer). You will own and evolve the data platform that powers clinica…
$160.56k - $193k
Role Description Lead Data Engineer, Fortune Brands Innovations Group, Inc., Deerfield, IL. ~Administer a cloud data warehouse platform (e.g., Snowflake or similar), including roles/permissions, performance tuning, secur…
$90k - $135k
Role Description As a Data Engineer at Wellbe you will play a pivotal role in collecting, processing, and analyzing large datasets to derive meaningful business insights. You will collaborate with cross-functional teams,…
$186.09k - $221.8k
Role Description The Data team at Babylist powers decision-making across the entire business — from product growth to operations to AI. This is a senior individual contributor role on the Data Engineering team, sitting a…
$100.1k - $167k
Role Description In this role you will have the chance to build large additions to our data engineering framework, contributing to an infrastructure that centralizes ETL logic and metric definitions. You will have autono…
Role Description We are looking for a Middle Data Engineer specialized in Azure Databricks to join our data platform team. The candidate will design and develop modern data pipelines and Lakehouse architectures, leveragi…
Role Description We're looking to hire a Data Migration Engineer to own the technical execution of data migrations that move customers from legacy systems into gaiia. You'll join the Migration Solutions team, which owns…
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What data engineers earn remotely
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $38–$52 | $78k–$108k |
| Mid level | $52–$72 | $108k–$150k |
| Senior | $70–$94 | $145k–$195k |
National ranges — remote pay usually tracks the employer's base market.
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What employers ask for
The skills these listings keep naming
SQL and data modelingPython or ScalaAirflow or similar orchestrationSpark or other batch processingWarehouses (Snowflake, BigQuery)dbtStreaming (Kafka)Data quality testingCloud infrastructure
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Interview questions worth rehearsing
With the thing the interviewer is actually listening for
Design a pipeline that loads data from a production database into a warehouse daily.
Cover extraction strategy, incremental loads versus full refresh, idempotency, and monitoring. Saying how you would backfill after a failure shows real pipeline experience.
How do you handle late-arriving or duplicate data?
Discuss idempotent upserts, watermarks, and dedup keys. This is a daily reality of the job, so a concrete example lands well.
Batch or streaming — how do you decide?
Anchor on the actual freshness requirement and cost. Most 'real-time' asks are fine at minutes; recognizing that is the mature answer.
A stakeholder says the numbers in their dashboard are wrong. Walk me through your debugging.
Trace lineage from the dashboard back to the source, isolating which layer diverged. Showing calm, structured lineage-tracing is the point of the question.
How do you model data for analytics — star schema, wide tables, something else?
Show you know the classic patterns and modern warehouse economics, and that you choose based on query patterns and team skill, not doctrine.
How do you test data pipelines?
Talk about schema and freshness checks, row-count and distribution tests, and tools like dbt tests or Great Expectations — plus alerting when they fail.
Tell me about a pipeline that failed badly and what you changed.
Structure it like an incident review: impact, cause, fix, prevention. Emphasize the durable improvement, such as monitoring or contract enforcement.
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Resume tips that move the needle
For data engineers specifically — generic advice costs you here
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State data scale plainly — rows per day, terabytes managed, pipeline counts — because it is the first thing hiring managers scan for.
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Name your orchestration, processing, and warehouse tools per role; the modern stack (Airflow, dbt, Snowflake) is a keyword screen.
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Highlight reliability outcomes: pipeline failure rates, data freshness SLAs met, incident reductions.
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Show cost work if you have it — warehouse spend is a live concern and optimization stories differentiate.
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Mention who consumed your data (analysts, ML teams, executives) to show you build for users, not just movement.
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Where this role goes
Typical progression
01
Junior Data Engineer
02
Data Engineer
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Senior Data Engineer
04
Staff Data Engineer
05
Data Platform Lead
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