Data Engineer Jobs
Data Engineer jobs are open across fintech, healthtech, e-commerce, media, and enterprise software, from entry-level to staff and principal, with specializations in data pipeline architecture, cloud infrastructure, and streaming systems. Find a role that fits from the openings below and apply directly.
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Showing 5 of 15,508+ Data Engineer jobs
About us
Beast Industries is a multifaceted media and entertainment company founded by Jimmy Donaldson, popularly known as MrBeast, the most watched person in the world. Renowned for revolutionizing digital content creation, Beast Industries encompasses a diverse portfolio of ventures that extend far beyond its origins on YouTube. With a mission to entertain, inspire, and create significant social impact, Beast Industries operates across various domains including digital media, philanthropy, consumer products, and innovative business initiatives. At Beast Industries, we believe in the transformative power of digital media and its potential to entertain, educate, and effect positive change. Our commitment to innovation, creativity, and philanthropy drives us to explore new frontiers, create unforgettable experiences, and build a legacy that inspires future generations.
BEAST INDUSTRIES
Senior Data Engineer
Location: Primary: Bay Area (San Francisco / Peninsula) | Secondary: NYC
The Opportunity
We're doing an AI-first engineering rebuild for a company that already has an audience of 100M+ people. This is a zero-to-one build with no legacy constraints, so you get to design the data platform from scratch instead of untangling years of pipelines. You're here to build the privacy-safe data foundation that powers everything from product to AI.
The Product
You'll design, build, and run the data platform behind the MrBeast ecosystem: the foundation that lets us understand our audience and power great experiences, directly and with partners. That means:
- Build scalable batch and real-time pipelines feeding analytics, reporting, ML, and operational decisions.
- Hit 99.9%+ pipeline availability and cut data delivery latency on critical datasets.
- Build a privacy-safe data foundation that powers AI and product work across the company.
- Design and implement scalable batch and streaming data pipelines.
- Develop and maintain enterprise data models, schemas, and storage architectures.
- Optimize data processing for performance, reliability, and cost.
- Build automated testing, monitoring, observability, and alerting for data systems.
- Partner with stakeholders to turn business requirements into technical data solutions.
- Set and promote data engineering standards, governance, and best practices, and drive adoption.
- Troubleshoot complex platform issues and production incidents, and mentor engineers through design reviews.
Who You Are
- AI-Native: You're already using AI in your workflow, and you build the data foundations that modern AI and ML actually run on.
- Platform Builder: Typically 8+ years designing and operating production-grade data platforms, with strong data modeling, ETL/ELT, and distributed data processing chops.
- Reliability + Quality Focused: You've driven real improvements in pipeline reliability and data quality, and you can measure and sustain them.
- Independent Leader: You lead complex technical initiatives on your own and take ownership from design through operational support. Experience building cloud-based data solutions and modern data architectures. Bonus points for supporting ML and AI data workflows, streaming and event-driven architectures, data governance and metadata management, and leading technical communities of practice.
Benefits
- Equity: Highly competitive equity package designed for a foundational hire.
- Hybrid Model: Expected: 2 days per week in-office (Bay Area or NYC).
The Perks, Why Work On the MrBeast Team
We are redefining what entertainment and storytelling look like at global scale. Every piece of content we publish reaches millions and influences culture in real time. This is your opportunity to lead the team that decides how those moments come to life across every screen.
- Competitive Salary
- Generous Medical (Blue Cross Blue Shield), Dental, Vision and company-paid Life Insurance
- Company contributions to employee Health Savings Accounts (HSA)
- 401k Plan with Safe Harbor company-matching
- Flexible vacation policy and paid company holidays
- Company-provided technology package
- Relocation assistance where applicable, including travel and company-provided housing for the first 90 days
About us
Beast Industries is a multifaceted media and entertainment company founded by Jimmy Donaldson, popularly known as MrBeast, the most watched person in the world. Renowned for revolutionizing digital content creation, Beast Industries encompasses a diverse portfolio of ventures that extend far beyond its origins on YouTube. With a mission to entertain, inspire, and create significant social impact, Beast Industries operates across various domains including digital media, philanthropy, consumer products, and innovative business initiatives. At Beast Industries, we believe in the transformative power of digital media and its potential to entertain, educate, and effect positive change. Our commitment to innovation, creativity, and philanthropy drives us to explore new frontiers, create unforgettable experiences, and build a legacy that inspires future generations.
BEAST INDUSTRIES
Senior Data Engineer
Location: Primary: Bay Area (San Francisco / Peninsula) | Secondary: NYC
The Opportunity
We're doing an AI-first engineering rebuild for a company that already has an audience of 100M+ people. This is a zero-to-one build with no legacy constraints, so you get to design the data platform from scratch instead of untangling years of pipelines. You're here to build the privacy-safe data foundation that powers everything from product to AI.
The Product
You'll design, build, and run the data platform behind the MrBeast ecosystem: the foundation that lets us understand our audience and power great experiences, directly and with partners. That means:
- Build scalable batch and real-time pipelines feeding analytics, reporting, ML, and operational decisions.
- Hit 99.9%+ pipeline availability and cut data delivery latency on critical datasets.
- Build a privacy-safe data foundation that powers AI and product work across the company.
- Design and implement scalable batch and streaming data pipelines.
- Develop and maintain enterprise data models, schemas, and storage architectures.
- Optimize data processing for performance, reliability, and cost.
- Build automated testing, monitoring, observability, and alerting for data systems.
- Partner with stakeholders to turn business requirements into technical data solutions.
- Set and promote data engineering standards, governance, and best practices, and drive adoption.
- Troubleshoot complex platform issues and production incidents, and mentor engineers through design reviews.
Who You Are
- AI-Native: You're already using AI in your workflow, and you build the data foundations that modern AI and ML actually run on.
- Platform Builder: Typically 8+ years designing and operating production-grade data platforms, with strong data modeling, ETL/ELT, and distributed data processing chops.
- Reliability + Quality Focused: You've driven real improvements in pipeline reliability and data quality, and you can measure and sustain them.
- Independent Leader: You lead complex technical initiatives on your own and take ownership from design through operational support. Experience building cloud-based data solutions and modern data architectures. Bonus points for supporting ML and AI data workflows, streaming and event-driven architectures, data governance and metadata management, and leading technical communities of practice.
Benefits
- Equity: Highly competitive equity package designed for a foundational hire.
- Hybrid Model: Expected: 2 days per week in-office (Bay Area or NYC).
The Perks, Why Work On the MrBeast Team
We are redefining what entertainment and storytelling look like at global scale. Every piece of content we publish reaches millions and influences culture in real time. This is your opportunity to lead the team that decides how those moments come to life across every screen.
- Competitive Salary
- Generous Medical (Blue Cross Blue Shield), Dental, Vision and company-paid Life Insurance
- Company contributions to employee Health Savings Accounts (HSA)
- 401k Plan with Safe Harbor company-matching
- Flexible vacation policy and paid company holidays
- Company-provided technology package
- Relocation assistance where applicable, including travel and company-provided housing for the first 90 days
See All 15,508+ Data Engineer Jobs
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Find Data Engineer JobsData Engineer Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- Apple638
- Amazon610
- NVIDIA403
- Tata Consultancy Services (TCS)313
- CVS Health240
Top Industries Hiring
- Technology & Software6,536
- Consulting & Professional Services1,339
- Electronics & Hardware1,142
- Banking & Financial Services817
- Healthcare & Medical Services578
What Employers Look For
The qualifications that appear most often in data engineer jobs.
- Proficiency in SQL and at least one scripting language such as Python or Scala
- Hands-on experience with cloud data platforms like AWS, GCP, or Azure
- Experience building and maintaining ETL or ELT pipelines in production
- Familiarity with orchestration tools such as Apache Airflow or Prefect
- Bachelor's degree in computer science, engineering, or a related technical field
- Experience with columnar or distributed data warehouses such as Snowflake, BigQuery, or Redshift
Tips for Your Data Engineer Job Search
Tailor your resume to the stack
Data engineer job descriptions vary significantly by stack. Rewrite your resume bullets to mirror the tools listed in each posting, whether that's Spark, dbt, Airflow, or Snowflake, so your experience reads as a direct match rather than a general fit.
Show pipeline work, not just queries
Hiring managers want to see that you build and maintain data infrastructure, not just consume it. Highlight projects where you designed ingestion workflows, handled schema evolution, or reduced pipeline latency, with specific outcomes wherever you can name them.
Apply early to roles that fit
Migrate Mate lists data engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target companies by data maturity stage
A startup building its first warehouse and a Fortune 500 modernizing legacy ETL need very different skills. Read job descriptions for clues about data maturity, such as greenfield builds versus migrations, and lead your cover note with experience that matches that stage.
Prepare a systems design answer for the interview
Most data engineer interviews include at least one open-ended design question, like architecting a batch pipeline or a real-time event stream. Practice walking through trade-offs out loud, covering ingestion, transformation, storage, and orchestration choices, not just the final architecture.
Negotiate with competing offer context
If you hold more than one offer, share that fact during negotiation. Compensation for data engineers varies by specialization and cloud platform, so a competing offer in a similar stack gives you grounded leverage without needing to justify a number from scratch.
Data Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most data engineers?
The companies hiring the most data engineers right now include Apple, Amazon, and NVIDIA, with the largest share of openings in California, Texas, and New York, based on current listings on Migrate Mate as of June 2026. Demand is concentrated in technology, financial services, and healthcare, where data infrastructure work tends to be ongoing rather than project-based.
How many data engineer jobs are remote?
About 28% of data engineer openings are fully remote or hybrid as of June 2026, making it one of the more remote-accessible engineering roles in tech. Pipeline and platform engineering work is especially likely to be remote, while roles with heavy cross-functional collaboration or on-premise data infrastructure tend to require more in-office time.
How do you become a data engineer?
Start by building a solid foundation in SQL and Python, then learn how data moves through a pipeline by working with an orchestration tool like Airflow and a cloud warehouse like Snowflake or BigQuery. Build two or three portfolio projects that show end-to-end pipeline work, document them on GitHub, and apply to junior or associate data engineer roles. Many people enter the field from adjacent roles in analytics or software engineering, so prior technical experience accelerates the transition.
Can you get a data engineer job with little experience?
Yes, entry-level data engineer roles exist, and employers often hire candidates who demonstrate practical pipeline skills even without a long employment history. Build portfolio projects that show you can ingest, transform, and serve data reliably, use cloud-free tools like DuckDB or SQLite to keep costs down, and target companies that are still building out their data infrastructure, since those teams are more likely to invest in developing junior engineers.
What does the data engineer interview process look like?
Most data engineer interviews include a recruiter screen, a technical phone interview covering SQL and Python fundamentals, and at least one systems design round where you walk through how you would build or scale a pipeline. Later rounds often involve a take-home or live coding exercise focused on data transformation or pipeline logic. Final rounds typically include a team fit conversation and, at some companies, a review of your past architecture decisions.
Where can I find and apply to data engineer jobs?
You can find and apply to data engineer jobs on Migrate Mate, which lists current openings from employers across the United States. Search the listings to find roles that match your stack and experience level, then apply directly to each one that fits.
See All 15,508+ Data Engineer Jobs
Jump back to the full list of openings and apply to any data engineer role that fits.
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