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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As a databricks engineer, you will help design, build, and support data management solutions that enable reliable, scalable, and secure use of data across business and technology functions. In this role, you will collaborate with cross-functional stakeholders to develop data pipelines, improve data quality, and support data governance and integration efforts. The ideal candidate brings hands-on experience in data engineering and the ability to manage multiple priorities in a dynamic environment.
Work you'll do
As a US Delivery Center Senior Consultant, Data Engineering and Conversion Solutions on the team, you will:
- Design, build, test, and maintain data pipelines and data integration solutions
- Support data modeling, transformation, and storage processes across structured and unstructured data sources
- Monitor data workflows, troubleshoot issues, and implement fixes to improve reliability and performance
- Collaborate with business, analytics, and technology teams to define data requirements and support delivery priorities
- Apply data quality, metadata, and governance standards across data assets and processes
A successful candidate would possess these skills:
- Ability to work independently and collaborate as part of a team
- Effective written and verbal communication skills
- Meticulous attention to detail and quality of work product
- Ability to build and sustain professional relationships
- Ability to lead projects or workstreams
- Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
- Strong interpersonal skills and professional demeanor
- Ability to meet deadlines
- Ability to provide clear guidance to others
The team
Deloitte's Government & Public Services (GPS) practice - our people, ideas, technology and outcomes - is designed for impact. Serving federal, state, & local government clients as well as public higher education institutions, our team of professionals brings fresh perspective to help clients anticipate disruption, reimagine the possible, and fulfill their mission promise.
Our AI & Data offering provides a full spectrum of solutions for designing, developing, and operating cutting-edge Data and AI platforms, products, insights, and services. Our offerings help clients innovate, enhance and operate their data, AI, and analytics capabilities, ensuring they can mature and scale effectively.
This opportunity sits within our Deloitte US Delivery Center model, which is dedicated to driving impactful business services. It leverages Deloitte's scale and talent, as well as a center delivery model to provide high-quality, cost-effective service with standardized processes and procedures to service businesses across Deloitte.
The Deloitte US Delivery Center has a small-business feel with a big-business impact. With the resources of Deloitte and a community feel, the delivery center model provides high-quality services to our clients. USDC professionals work out of one of our specific delivery center locations, and each location presents dynamic career opportunities for professionals to focus on their work with nominal travel requirements.
Qualifications
Required:
- Bachelor's degree required
- Must be able to obtain and maintain the required clearance for this role
- 2+ years of experience in data engineering, data integration, or data management, including 2+ years of experience with Structured Query Language (SQL)
- 2+ years of experience building or supporting extract, transform, and load (ETL) or extract, load, and transform (ELT) pipelines
- 2+ years of experience with Python and PySpark
- 1+ years of experience with Databricks and cloud-based data platforms, including data pipeline development and data transformation
- Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
- Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future
Preferred:
- Experience with data warehousing concepts and dimensional data modeling
- Experience with data quality, metadata, or data governance processes
- Experience working with application programming interfaces (APIs) and system integrations
- Experience supporting Agile delivery teams
- Experience in a professional services environment
- Hybrid Work Model: Operate under a hybrid system requiring residence within a commutable distance to one of the US Delivery Center locations
- Co-location Expectation: Spend up to 30% of working time co-located at an assigned office for orchestrated opportunities, including projects, practice sessions, training, and Moments That Matter at a Deloitte Delivery Center location, Geo-Hub location, approved site, or project location
As a databricks engineer, you will help design, build, and support data management solutions that enable reliable, scalable, and secure use of data across business and technology functions. In this role, you will collaborate with cross-functional stakeholders to develop data pipelines, improve data quality, and support data governance and integration efforts. The ideal candidate brings hands-on experience in data engineering and the ability to manage multiple priorities in a dynamic environment.
Work you'll do
As a US Delivery Center Senior Consultant, Data Engineering and Conversion Solutions on the team, you will:
- Design, build, test, and maintain data pipelines and data integration solutions
- Support data modeling, transformation, and storage processes across structured and unstructured data sources
- Monitor data workflows, troubleshoot issues, and implement fixes to improve reliability and performance
- Collaborate with business, analytics, and technology teams to define data requirements and support delivery priorities
- Apply data quality, metadata, and governance standards across data assets and processes
A successful candidate would possess these skills:
- Ability to work independently and collaborate as part of a team
- Effective written and verbal communication skills
- Meticulous attention to detail and quality of work product
- Ability to build and sustain professional relationships
- Ability to lead projects or workstreams
- Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
- Strong interpersonal skills and professional demeanor
- Ability to meet deadlines
- Ability to provide clear guidance to others
The team
Deloitte's Government & Public Services (GPS) practice - our people, ideas, technology and outcomes - is designed for impact. Serving federal, state, & local government clients as well as public higher education institutions, our team of professionals brings fresh perspective to help clients anticipate disruption, reimagine the possible, and fulfill their mission promise.
Our AI & Data offering provides a full spectrum of solutions for designing, developing, and operating cutting-edge Data and AI platforms, products, insights, and services. Our offerings help clients innovate, enhance and operate their data, AI, and analytics capabilities, ensuring they can mature and scale effectively.
This opportunity sits within our Deloitte US Delivery Center model, which is dedicated to driving impactful business services. It leverages Deloitte's scale and talent, as well as a center delivery model to provide high-quality, cost-effective service with standardized processes and procedures to service businesses across Deloitte.
The Deloitte US Delivery Center has a small-business feel with a big-business impact. With the resources of Deloitte and a community feel, the delivery center model provides high-quality services to our clients. USDC professionals work out of one of our specific delivery center locations, and each location presents dynamic career opportunities for professionals to focus on their work with nominal travel requirements.
Qualifications
Required:
- Bachelor's degree required
- Must be able to obtain and maintain the required clearance for this role
- 2+ years of experience in data engineering, data integration, or data management, including 2+ years of experience with Structured Query Language (SQL)
- 2+ years of experience building or supporting extract, transform, and load (ETL) or extract, load, and transform (ELT) pipelines
- 2+ years of experience with Python and PySpark
- 1+ years of experience with Databricks and cloud-based data platforms, including data pipeline development and data transformation
- Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
- Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future
Preferred:
- Experience with data warehousing concepts and dimensional data modeling
- Experience with data quality, metadata, or data governance processes
- Experience working with application programming interfaces (APIs) and system integrations
- Experience supporting Agile delivery teams
- Experience in a professional services environment
- Hybrid Work Model: Operate under a hybrid system requiring residence within a commutable distance to one of the US Delivery Center locations
- Co-location Expectation: Spend up to 30% of working time co-located at an assigned office for orchestrated opportunities, including projects, practice sessions, training, and Moments That Matter at a Deloitte Delivery Center location, Geo-Hub location, approved site, or project location
Data Engineer Jobs by Experience Level
Top Cities Hiring Data Engineers
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Find Data Engineer JobsData Engineer Job Market
Who's Hiring
- Speechify231
- Amazon133
- Google95
- Apple68
- Booz Allen Hamilton49
Top Industries Hiring
- Technology & Software193
- Consulting & Professional Services23
- Insurance19
- Investment & Asset Management15
- Medical Devices11
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 Speechify, Amazon, and Google, with the largest share of openings in California, Texas, and Virginia, based on current listings on Migrate Mate as of August 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 78% of data engineer openings are fully remote or hybrid as of August 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 3,793+ Data Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
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