Senior Level Data Integration Engineer Jobs
Senior level data integration engineer jobs place experienced engineers in charge of integration architecture decisions, pipeline reliability, and the cross-functional teams that deliver them. Openings concentrate across Technology & Software, Staffing & Recruiting, and Banking & Financial Services, with 67% of roles available remote or hybrid, and employers like KBR, Apex IT, and Algoworks hiring at this level now.
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Role overview
We are looking for a Senior Data Integration Engineer to design, implement, and operate reliable integrations between a cloud data platform and an established data-processing application. The role will focus on building production-grade integration solutions, ensuring data consistency, compatibility, traceability and seamless processing across multiple services.
Key responsibilities:
- Design and implement source-to-application integrations, adapters and data transformation workflows.
- Develop and maintain batch and change-data processing pipelines using Python and SQL.
- Work with APIs, XML/JSON and integration services to enable reliable data exchange.
- Ensure record identity, data consistency and compatibility with existing applications.
- Implement robust logging, monitoring, retries, error handling and replay mechanisms.
- Develop automated tests and validate integrations across multiple services.
- Troubleshoot end-to-end data flows and trace individual records across systems.
- Evaluate and recommend whether to modify existing applications, introduce adapters, or use shared data models.
- Collaborate with engineering teams to ensure reliable, maintainable and production-ready integration solutions.
Required skills and qualifications:
- 9+ years of experience building and operating production-grade data integrations.
- Strong hands-on experience with Python and SQL.
- Experience working with REST APIs and data formats such as XML and JSON.
- Strong understanding of batch processing and change-data processing.
- Experience developing integration adapters and transformation workflows.
- Hands-on experience with automated testing, logging, retries and replay mechanisms.
- Ability to troubleshoot and trace data across multiple services and processing layers.
Must have skills:
- Python and SQL
- API and data processing
- XML/JSON
- Batch and change-data processing
- Integration adapters and data transformations
- Automated testing
- Error handling, logging, retry and replay
- Strong understanding of end-to-end data flow and record traceability
Good to have skills:
- Experience with AWS Cloud services.
- Hands-on experience with RabbitMQ.
- Experience with MongoDB and Solr.
- Knowledge of cloud-based data platforms and distributed systems.
- Familiarity with CI/CD and DevOps practices.
Desired attributes:
- Strong problem-solving and troubleshooting skills.
- Ability to make sound architectural decisions around adapters, application changes and shared models.
- Strong focus on data accuracy, reliability and system compatibility.
- Excellent communication and collaboration skills.
- Ability to work independently and take end-to-end ownership of integration solutions.
- Strong engineering mindset with a focus on maintainability, testability and production readiness.
Interview process
- 2 rounds of discussion.
Role overview
We are looking for a Senior Data Integration Engineer to design, implement, and operate reliable integrations between a cloud data platform and an established data-processing application. The role will focus on building production-grade integration solutions, ensuring data consistency, compatibility, traceability and seamless processing across multiple services.
Key responsibilities:
- Design and implement source-to-application integrations, adapters and data transformation workflows.
- Develop and maintain batch and change-data processing pipelines using Python and SQL.
- Work with APIs, XML/JSON and integration services to enable reliable data exchange.
- Ensure record identity, data consistency and compatibility with existing applications.
- Implement robust logging, monitoring, retries, error handling and replay mechanisms.
- Develop automated tests and validate integrations across multiple services.
- Troubleshoot end-to-end data flows and trace individual records across systems.
- Evaluate and recommend whether to modify existing applications, introduce adapters, or use shared data models.
- Collaborate with engineering teams to ensure reliable, maintainable and production-ready integration solutions.
Required skills and qualifications:
- 9+ years of experience building and operating production-grade data integrations.
- Strong hands-on experience with Python and SQL.
- Experience working with REST APIs and data formats such as XML and JSON.
- Strong understanding of batch processing and change-data processing.
- Experience developing integration adapters and transformation workflows.
- Hands-on experience with automated testing, logging, retries and replay mechanisms.
- Ability to troubleshoot and trace data across multiple services and processing layers.
Must have skills:
- Python and SQL
- API and data processing
- XML/JSON
- Batch and change-data processing
- Integration adapters and data transformations
- Automated testing
- Error handling, logging, retry and replay
- Strong understanding of end-to-end data flow and record traceability
Good to have skills:
- Experience with AWS Cloud services.
- Hands-on experience with RabbitMQ.
- Experience with MongoDB and Solr.
- Knowledge of cloud-based data platforms and distributed systems.
- Familiarity with CI/CD and DevOps practices.
Desired attributes:
- Strong problem-solving and troubleshooting skills.
- Ability to make sound architectural decisions around adapters, application changes and shared models.
- Strong focus on data accuracy, reliability and system compatibility.
- Excellent communication and collaboration skills.
- Ability to work independently and take end-to-end ownership of integration solutions.
- Strong engineering mindset with a focus on maintainability, testability and production readiness.
Interview process
- 2 rounds of discussion.
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Who's Hiring
Top Industries Hiring
- Technology & Software
- Staffing & Recruiting
- Banking & Financial Services
- Consulting & Professional Services
Senior Level Data Integration Engineer Jobs: Frequently Asked Questions
How do I get a senior level data integration engineer job?
Employers at this level look for engineers who have owned integration architecture end to end, not just contributed to it. Demonstrable experience designing scalable ETL and ELT pipelines, selecting integration platforms, resolving data quality issues at scale, and mentoring junior engineers all carry significant weight. Strong candidates can speak to tradeoffs they made on real systems and the business outcomes that followed.
Which companies hire senior level data integration engineers?
Companies hiring senior level data integration engineers right now include KBR, Apex IT, and Algoworks, based on current listings on Migrate Mate as of September 2026. Hiring at this level covers large enterprises managing complex data ecosystems, cloud-native technology firms, and professional services organizations building out data infrastructure for clients.
Are there remote senior level data integration engineer jobs?
Yes, remote and hybrid availability is strong at this level. About 67% of senior level data integration engineer openings are remote or hybrid as of September 2026, reflecting how readily distributed teams can collaborate on integration work. On-site roles do exist, typically where data governance, security requirements, or enterprise system access makes proximity necessary.
What makes a data integration engineer role senior level?
Senior level roles are defined by scope and ownership. Engineers at this stage are expected to set the technical direction for integration systems, evaluate and select tooling, establish data quality and pipeline standards, and take accountability for production reliability. They also mentor mid and junior engineers, contribute to architecture reviews, and collaborate directly with data engineering leadership and business stakeholders.
Which industries hire the most senior level data integration engineers?
Senior Level data integration engineer roles concentrate in Technology & Software, Staffing & Recruiting, and Banking & Financial Services, based on current listings on Migrate Mate as of September 2026. These sectors drive hiring at this level because their operations depend on reliable, high-volume data movement across complex systems, where experienced engineers are needed to design and own the infrastructure rather than simply maintain it.