Mid Level Data Engineer Jobs
Mid level data engineer jobs go to engineers ready to own pipelines end to end, drive architectural decisions with limited oversight, and bring junior teammates up to speed. Roles are split across on-site, remote, and hybrid settings in Technology & Software, Retail, and Consulting & Professional Services, with employers like Amazon, Apple, and Speechify hiring at this level now.
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INTRODUCTION
Are you passionate about making a difference in people's lives? Do you enjoy working in a service-oriented industry? If so, this opportunity may be the right fit for you!
At Modivcare, our mission is to connect people to the care they need. Every report, dashboard, operational workflow, and AI initiative starts with trusted data. As a Cloud Data Warehouse Engineer, you'll build scalable data pipelines, cloud data warehouse solutions, and transformation frameworks that enable smarter decisions and improve healthcare outcomes for millions of members.
We're looking for an experienced engineer with strong, hands-on dbt Core experience who enjoys building modern cloud data platforms and turning complex data into business value.
Your work will directly influence how business leaders, operations teams, and analytics partners make decisions every day. You'll help modernize our enterprise data platform by building trusted, scalable data products that improve reporting, enable self-service analytics, and support AI initiatives. This is an opportunity to solve complex technical challenges while making a measurable impact on the healthcare experience for the people we serve.
ROLE AND RESPONSIBILITIES
dbt Engineering & Data Transformation
- Design, develop, and maintain dbt projects, models, macros, snapshots, tests, and reusable transformation frameworks.
- Build and maintain enterprise data transformation pipelines using dbt Core and advanced SQL.
- Develop reusable business logic and data models that support reporting, self-service analytics, operational applications, and AI initiatives.
- Implement dbt best practices including modular design, testing, documentation, lineage tracking, and source control.
- Optimize dbt models and transformation workloads for performance, scalability, and maintainability.
- Support CI/CD deployment processes and automated testing for dbt projects.
- Collaborate with business and technical teams to translate requirements into scalable and reusable transformation logic.
Data Modeling & Data Warehouse Development
- Develop and maintain cloud data warehouse solutions using AWS services including Redshift, S3, Glue, Athena, Lambda, and Step Functions.
- Design and maintain dimensional data models supporting reporting, self-service analytics, and operational data needs.
- Build and maintain fact tables, dimensions, star schemas, snowflake schemas, and slowly changing dimensions (SCDs).
- Develop curated data marts and trusted datasets for reporting, analytics, and downstream applications.
- Partner with business and technical teams to translate requirements into scalable and reusable data models.
- Optimize data structures and query performance for large-scale analytical workloads.
- Follow established standards and best practices for data modeling, SQL development, and data warehouse design.
Data Engineering & Pipeline Development
- Design, build, and maintain batch and near real-time data pipelines supporting enterprise data integration requirements.
- Develop ELT/ETL workflows using AWS services, dbt, SQL, and Python.
- Integrate data from operational systems, APIs, SaaS applications, healthcare platforms, and third-party data providers.
- Support ingestion and transformation of structured, semi-structured, and unstructured data.
- Optimize data processing workflows for scalability, reliability, and cost efficiency.
- Troubleshoot and resolve data pipeline and data warehouse performance issues.
Collaboration & Delivery
- Partner with application teams, business stakeholders, BI developers, and analytics teams to understand data requirements.
- Deliver trusted and well-documented datasets that support reporting and self-service analytics.
- Participate in Agile development processes including sprint planning, estimation, code reviews, testing, and release management.
- Work effectively with remote and offshore teams to deliver data platform initiatives.
BASIC QUALIFICATIONS
- Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related field; equivalent combination of education and experience will be considered.
- Five (5) or more years of experience in data warehousing, cloud data engineering, or related data platform roles.
- Experience designing and developing enterprise cloud data warehouse solutions.
- Experience building enterprise ELT/ETL solutions and data integration pipelines.
- Experience working with modern cloud data warehouse environments.
- Experience supporting reporting, business intelligence, self-service analytics, and enterprise data platforms.
- Experience working in healthcare or another regulated industry is preferred.
- Strong hands-on experience with dbt Core, including development of models, macros, snapshots, tests, documentation, lineage, and reusable transformation frameworks.
- Advanced knowledge of SQL, including complex joins, window functions, common table expressions (CTEs), analytical transformations, query tuning, and performance optimization.
- Knowledge of dimensional data modeling techniques, including fact tables, dimensions, star schemas, snowflake schemas, and slowly changing dimensions (SCDs).
- Proficiency with Amazon Redshift and modern cloud data warehouse technologies.
- Knowledge of AWS cloud services, including Redshift, S3, Glue, Lambda, Athena, and Step Functions.
- Proficiency in Python for data engineering, automation, and scripting.
- Knowledge of Git, CI/CD, and modern software development best practices.
- Ability to design, develop, and optimize batch, micro-batch, and near real-time data pipelines.
- Ability to build curated data marts and trusted datasets that support reporting, self-service analytics, and downstream applications.
- Strong analytical, problem-solving, communication, collaboration, and organizational skills.
- Ability to work effectively in Agile environments and collaborate with remote and offshore teams.
COMPENSATION
- Salary: $97,200.00 – 140,000
The physical demands described are representative of those that must be met by an employee to successfully perform the essential functions of the position. Reasonable accommodations may be made to enable qualified individuals with disabilities to perform the essential functions of the job.
Primarily seated work; extensive computer and telephone use; occasional standing, walking, reaching, bending, and lifting up to 10 lbs.
Modivcare’s positions are posted and open for applications for a minimum of 5 days. Positions may be posted for a maximum of 45 days dependent on the type of role, the number of roles, and the number of applications received. We encourage our prospective candidates to submit their application(s) expediently so as not to miss out on our opportunities. We frequently post new opportunities and encourage prospective candidates to check back often for new postings.
BENEFITS
We value our team members and realize the importance of benefits for you and your family.
Modivcare offers a comprehensive benefits package to include the following:
- Medical, Dental, and Vision insurance
- Employer Paid Basic Life Insurance and AD&D
- Voluntary Life Insurance (Employee/Spouse/Child)
- Health Care and Dependent Care Flexible Spending Accounts
- Pre-Tax and Post-Tax Commuter and Parking Benefits
- 401(k) Retirement Savings Plan with Company Match
- Paid Time Off
- Paid Parental Leave
- Short-Term and Long-Term Disability
- Tuition Reimbursement
- Employee Discounts (retail, hotel, food, restaurants, car rental and much more!)
Modivcare is an Equal Opportunity Employer.
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Equal Opportunity Employer Minorities/Women/Protected Veterans/Disabled
We consider all applicants for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, handicap or disability, or status as a Vietnam-era or special disabled veteran in accordance with federal law. If you need assistance, please reach out to us at hr.recruiting@modivcare.com
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Who's Hiring
- Amazon38

- Apple20

- Speechify14

- TikTok8

- Esri7

Top Industries Hiring
- Technology & Software209
- Retail42
- Consulting & Professional Services38
- E-Commerce & Online Marketplaces33
- Electronics & Hardware28
Mid Level Data Engineer Jobs: Frequently Asked Questions
How do I get a mid level data engineer job?
Lead with ownership, not just participation. Highlight projects where you designed or rebuilt a pipeline, resolved production data quality issues, or introduced tooling that your team adopted. Interviewers at this level want evidence you can operate independently, so frame your experience around decisions you made and outcomes you delivered, not tasks you completed under close direction.
Which companies hire mid level data engineers?
Companies hiring mid level data engineers right now include Amazon, Apple, and Speechify, based on current listings on Migrate Mate as of August 2026. Hiring at this level covers large enterprises scaling their data platforms, mid-size technology companies building out their first dedicated data teams, and data-intensive firms in finance, healthcare, and retail.
Are there remote mid level data engineer jobs?
Yes, remote and hybrid options are widely available at this level. About 42% of mid level data engineer openings are remote or hybrid as of August 2026, reflecting how well data engineering work translates to distributed teams. Searching by location preference on Migrate Mate lets you filter current openings to match your preferred work setting.
How do I move up to a mid level data engineer role?
The shift from entry level to mid level comes from accumulating real ownership over time. Building depth in a core stack, taking the lead on a project rather than a single ticket, and demonstrating that your pipelines hold up in production are the markers employers look for. Measurable impact, such as improved reliability or reduced processing time, signals readiness more clearly than years alone.
Which industries hire the most mid level data engineers?
Mid Level data engineer roles concentrate in Technology & Software, Retail, and Consulting & Professional Services, based on current listings on Migrate Mate as of August 2026. These sectors tend to drive hiring at this level because they operate at the data volumes and complexity that require engineers who can own pipeline architecture rather than simply execute on pre-defined tasks.