Remote AI Data Engineer Jobs
Remote AI Data Engineer jobs are in active demand across the U.S., with remote-first firms and distributed teams hiring across technology, financial services, and healthcare. Employers hiring remotely right now include EPAM Systems, ZS Associates, and Penn Medicine. See the openings below and apply to the ones that match your experience.
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Job Overview
Vera is an AI services company. We are hiring a Mid-Level AI Data Engineer to work directly with clients: designing, building and maintaining their data warehouses on Azure, and using AI coding tools to deliver faster than a traditional consultancy. You typically run two or three client engagements at a time, some in build and some in maintenance, with design review and backing from the Lead Tech Engineer.
Duties
- Run discovery with client stakeholders, turn their source systems and reporting needs into a warehouse design and delivery plan, and present trade-offs in plain language.
- Design dimensional models (star schemas, slowly changing dimensions) and build warehouses on Azure SQL, Azure Synapse Analytics and Microsoft Fabric Warehouse, landing data in ADLS Gen2.
- Develop ELT pipelines with Azure Data Factory or Fabric pipelines from client sources such as ERP, CRM, SaaS APIs and flat files.
- Write and tune complex SQL: window functions, CTEs, stored procedures, indexing, partitioning and query-plan analysis.
- Set up security from day one: Entra ID access, row-level security, private endpoints and encryption.
- Maintain client warehouses after go-live: monitor pipeline runs, fix failures, handle source schema changes, and manage Azure cost and performance.
- Run data-quality checks, reconciliation against source systems and lineage so clients can trust their numbers.
- Handle support tickets and change requests within agreed SLAs, and keep clients informed about what happened and what you fixed.
- Use AI coding agents (Claude Code, GitHub Copilot, Cursor or similar) for most implementation: schemas, pipelines, SQL, tests and documentation. Review and harden everything AI produces before it reaches a client environment, and follow Vera's guardrails: code review, automated tests, CI/CD and migration checks.
- Write the documentation, runbooks and handover material clients keep after a build.
Experience
- 3+ years in data engineering, database development or BI, including at least one Azure data warehouse you built or maintained for real users.
- Strong SQL (T-SQL and/or PostgreSQL): dimensional modelling, window functions, CTEs, stored procedures, and tuning from an execution plan.
- Hands-on Azure data services: Azure SQL or Synapse, Azure Data Factory or Fabric pipelines, and ADLS Gen2.
- Client-facing skills: you can run a requirements call, explain a technical trade-off to a non-technical stakeholder, and write clear status updates and documentation.
- Daily use of AI coding tools to build working software quickly, with a project you can show, and a solid grasp of how LLMs work, where they fail, and how to use them responsibly with client data.
- Working Python and Git.
- Comfortable juggling several client engagements and priorities at once.
Details
- Team: AI services (client delivery), reporting to the Lead Tech Engineer
- Location: Mostly remote (US) with occasional travel to clients; candidates in or near Massachusetts or New Hampshire preferred
- Employment type: Full-time employee
- Pay: $70,000–$85,000 base salary, benefits and bonus depending on experience
- Work authorization: Must be authorized to work in the United States without employer sponsorship, now or in the future. Vera does not sponsor work visas for this role.
How to apply
Apply through Indeed, or send your CV to jobs@verascale.com. Either way, include a short note on one Azure data warehouse you built or maintained, and how you used AI tools on it: what you specified, what the AI wrote, and what you had to fix.
Pay: $70,000.00 - $85,000.00 per year
Benefits:
- 401(k)
- Dental insurance
- Flexible schedule
- Flexible spending account
- Health insurance
- Life insurance
- Professional development assistance
- Retirement plan
- Vision insurance
Application Question(s):
- Are you authorized to work in the United States without employer sponsorship, now or in the future?
- How many years of data engineering, database or BI experience do you have?
- Which AI coding tools do you use regularly (Claude Code, GitHub Copilot, Cursor, other)?
- How many years of hands-on experience do you have with Azure data services
Work Location: Remote
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Who's Hiring
Top Industries Hiring
- Technology & Software
- Consulting & Professional Services
- Manufacturing
- Education
- Insurance
What Employers Look For
The qualifications that appear most often in remote AI data engineer jobs.
- Proficiency in Python and SQL for data pipeline development and transformation
- Experience building and maintaining ML feature pipelines or data platforms at scale
- Hands-on work with orchestration tools such as Apache Airflow, Prefect, or Dagster
- Familiarity with cloud data platforms including AWS, GCP, or Azure data services
- Knowledge of streaming frameworks such as Apache Kafka or Apache Flink
- Bachelor's degree in computer science, data engineering, or a related technical field
Tips for Your Remote AI Data Engineer Job Search
Show async collaboration in your portfolio
Remote employers want evidence you can work without constant check-ins. Document your projects with written READMEs, architecture decision records, and inline comments, because that's the kind of self-explaining output distributed teams depend on from a remote ai data engineer.
Apply early to remote roles that fit
Migrate Mate lists remote ai data engineer openings from across the U.S. in one place, so you can find roles that match your stack and apply directly without sorting through irrelevant on-site listings.
Highlight your remote AI toolchain explicitly
Call out the specific tools you use for distributed AI workflows, such as MLflow for experiment tracking, Airflow for orchestration, or dbt for transformation, because remote hiring managers scan for these to judge whether you'll ramp up without in-person training.
Prepare for async-style remote interviews
Many remote teams use take-home assessments or recorded video answers before any live call. Practice explaining your pipeline design decisions in writing and on camera, since remote ai data engineer interviews often weigh your communication clarity as much as your technical output.
Remote AI Data Engineer Jobs: Frequently Asked Questions
How do I get a remote ai data engineer job?
Target companies built on distributed teams, such as remote-first software firms and cloud-native startups, because they already have the infrastructure for async collaboration. Remote employers screen hard for self-direction, clear written communication, and hands-on proficiency with tools like dbt, Spark, Airflow, and vector databases. A public GitHub repo or portfolio project that shows an end-to-end AI pipeline gives you a concrete edge over candidates who only list skills.
Which companies hire remote ai data engineers?
Employers currently hiring remote ai data engineers include EPAM Systems, ZS Associates, and Penn Medicine, per current remote listings on Migrate Mate as of November 2026. Remote-first technology firms, fintech scale-ups, and distributed healthcare data teams make up the bulk of hiring for this role.
Can you get a remote ai data engineer job with no experience?
Yes, but remote entry-level roles are harder to land because you're expected to work independently from day one without in-office support. Remote-first startups and smaller distributed teams are more open to junior candidates than large enterprises. Build a demonstrable project, such as a deployed ML pipeline or a public data transformation repo, to show you can execute without hand-holding, and that's often what opens the door.
Do you need a degree for remote ai data engineer jobs?
Not always. Remote employers place significant weight on demonstrated skills, real project output, and familiarity with the modern AI and data stack over formal credentials. A strong portfolio, proficiency in Python, SQL, and ML frameworks, and evidence of shipping production-grade pipelines can carry more weight than a degree, particularly at remote-first companies that evaluate candidates on async work samples.
Which industries hire the most remote ai data engineers?
Remote ai data engineer roles concentrate in Technology & Software, Consulting & Professional Services, and Manufacturing, based on current remote listings on Migrate Mate as of November 2026. Those sectors rely on distributed data teams to build and maintain AI pipelines that don't require anyone to be physically on-site.
See All 166+ Remote AI Data Engineer Jobs
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Find Remote AI Data Engineer Jobs