Mid Level Data Operations Engineer Jobs
Mid level data operations engineer jobs go to engineers ready to own pipelines end to end, make architecture decisions with limited oversight, and mentor junior teammates through production issues. Openings are split across on-site, hybrid, and remote settings in Electronics & Hardware, Technology & Software, and Consulting & Professional Services, with Apple, Amazon, and Rivian hiring at this level now.
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Data Operations Engineer
W2 contract, min of 6 months
HYBRID out of Atlanta, GA; Dallas, TX; Houston, TX; Auburn Hills, MI
Target W2 $36/hr
Reporting to the Director Enterprise Data Management, the Engineer, Data Operations designs, develops, and operates secure, scalable, and high performing data and infrastructure solutions supporting a nationwide auto finance organization. This role serves as a technical contributor within the infrastructure team, driving data pipeline development, ETL optimization, and warehouse modernization across SQL Server, Azure Data Factory, and Microsoft Fabric, as well as the enterprise servers, storage, and software-defined cloud and network environments that underpin them. The Engineer, Data Operations partners with analytics, application, security, and operations teams to ensure data and infrastructure solutions align with enterprise architecture, regulatory requirements, and business objectives.
Essential Duties And Responsibilities
- Design, Develop, and Implement Data and ETL Solutions & Integrations – Assist in the design, development, and implementation of data solutions and integrations to optimize performance, scalability, and reliability.
- Monitor, Troubleshoot, and Resolve Problems – Implement and support effective monitoring to proactively identify and resolve issues, conducting effective root-cause analysis to address underlying problems and prevent recurrence.
- Provide Support & Optimization – Offer expertise in diagnosing and resolving issues by implementing the necessary corrective actions and/or fixes, ensuring the operational efficiency, reliability, and scalability of data systems and ETL processes.
- Document Technical Processes & Solutions – Maintain documentation for process and system configurations, engineering designs, and troubleshooting procedures to support knowledge sharing and ensure continuity of operations.
- Collaborate on Cross-Functional Projects – Work with team members and other departments to support business and technology initiatives and integrations, drive innovation, and improve workflows.
- Support Initiatives, Timelines, Budgets, and Deliverables – Support initiatives, timelines, budgets, and deliverables as assigned to ensure successful outcomes, managing priorities and resources effectively to meet business objectives.
- Data Analytics & Performance Monitoring – Collect data to track key metrics (KPIs, SLAs, and SLOs) and identify areas of risk and/or improvement using standard methodologies to deliver value to business partners.
- Ensures Business Alignment – Work closely with Product and/or Process Engineering team members to implement technical solutions with business partners that align with business goals using standard methodologies.
- Develop solutions to retrieve and process vendor data feeds, applying ETL processes to ensure efficient ingestion into enterprise staging systems.
- Develop T-SQL code to transform staging data from multiple vendors into a cohesive, business aligned warehouse structure, applying logic to enhance clarity and usability.
- Develop solutions to extract and transform data from the warehouse, applying customer specific business logic to create and deliver tailored datasets for internal and external consumers.
- Monitor, analyze, and optimize long-running T-SQL processes, applying performance tuning techniques to improve efficiency and ensure timely completion.
- Develop and/or contribute to the Enterprise Data Dictionary.
- Additional duties may be added as business needs evolve.
Qualifications
- Bachelor’s degree in Computer Science, Information Technology, or a related field, or an equivalent combination of education and relevant professional experience.
- Minimum of five years of experience in SQL development and support, with strong SQL Server fundamentals.
- Solid understanding of ETL development with SSIS workflows.
- Experience with Azure SQL setup and configuration, and Azure Data Factory (pipelines, activities, datasets, linked services, data flows, and integration runtimes), and Microsoft Fabric.
- Strong understanding of database systems monitoring and support, software best practices, and development methodologies.
- Experience with FTP tools for file transfer.
- DBA experience across SQL Server, Azure SQL, Fabric, Snowflake, and Redis Cache.
- Problem-Solving & Critical Thinking – Ability to analyze, troubleshoot, and develop solutions for complex issues and challenges, including troubleshooting in a multi-tier environment, supported by strong analytical and diagnostic skills.
- Design & Architecture – Knowledge of designing scalable, efficient, and secure data and ETL solutions.
- Automation – Proficiency in common database technologies (on-prem and cloud) and ETL tools, along with scripting and automation languages/tools, including T-SQL, cloud data factory, and data pipelines.
- Business & System Analysis – Ability to translate business requirements into high-level designs and technical specifications as needed.
- Database Optimization – Ability to analyze query execution plans and optimize database code, perform database maintenance and indexing, and conduct code reviews.
- Documentation & Communication – Ability to document processes, requirements, and troubleshooting steps clearly using industry-standard methodologies and formats, with strong communication skills to collaborate effectively with technical and non-technical stakeholders.
- Collaboration & Cross-Functional Work – Experience working with teams across different disciplines to integrate and optimize solutions.
- Frameworks & Methodologies – Experience utilizing relevant frameworks and methodologies to standardize solutions across on-prem and cloud database environments.
- Expertise in SQL Server (on-prem and cloud), with familiarity in Microsoft Fabric and Azure Data Factory.
- Proficiency in designing and managing data ingestion pipelines, ETL/ELT processes, metadata management, and automation of data flows across hybrid environments.
- Experience in building, optimizing, and managing data pipelines using Azure Fabric, ADF, and other data integration tools for efficient data movement and transformation. Ability to support BI and analytics teams by providing well-structured data models and optimized datasets for tools such as Power BI and Tableau.
- Cloud database experience across Azure SQL, Fabric, Redis Cache, Cosmos DB, and Snowflake.
- File Transfer – Ability to use FTP tools to transfer files.
- Strong time-management and problem-solving skills, with the ability to work with minimal supervision as a critical thinker and team player.
- Must have reliable transportation and live within a commutable distance to one of the following cities: Atlanta, GA; Dallas, TX; Houston, TX; Auburn Hills, MI.
PREFERRED QUALIFICATIONS
- Prior experience in financial services, auto lending, or other highly regulated industries strongly preferred.
- Master’s degree in a STEM discipline or Business Administration is a plus.
- Experience with Cosmos DB is a plus.
- One or more relevant certifications are preferred.
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Mid Level Data Operations Engineer Jobs: Frequently Asked Questions
How do I get a mid level data operations engineer job?
Position yourself around ownership, not just contribution. Highlight projects where you led the solution, debugged production incidents independently, or improved pipeline reliability in a measurable way. Tailor your resume to show progression in scope, name the specific tools you have worked with at scale, and be ready to discuss tradeoff decisions you made without waiting for a senior engineer to sign off.
Which companies hire mid level data operations engineers?
Companies hiring mid level data operations engineers right now include Apple, Amazon, and Rivian, based on current listings on Migrate Mate as of November 2026. At this level, hiring comes from a wide range of organizations, including technology platforms, financial services firms, and large enterprise companies that run complex internal data infrastructure.
Are there remote mid level data operations engineer jobs?
Yes, remote and hybrid options are common at this level. About 13% of mid level data operations engineer openings are remote or hybrid as of November 2026, reflecting strong employer demand for experienced engineers who can work independently without daily in-person oversight. On-site roles tend to cluster at companies with regulated data environments or hands-on infrastructure requirements.
How do I move up to a mid level data operations engineer role?
Moving from entry level to mid level takes deliberate depth-building. Focus on owning a component of a production system end to end, not just completing tickets. Develop fluency in at least one orchestration framework, one cloud data platform, and observability tooling. Document measurable outcomes from your work, take on incidents proactively, and demonstrate that you can unblock yourself and others before asking for guidance.
Which industries hire the most mid level data operations engineers?
Mid Level data operations engineer roles concentrate in Electronics & Hardware, Technology & Software, and Consulting & Professional Services, based on current listings on Migrate Mate as of November 2026. These sectors invest heavily in data infrastructure at scale, which creates sustained demand for mid level engineers who can maintain reliability, support analytics pipelines, and drive operational improvements without full senior-level supervision.