Senior Data Engineer

Posted 27d ago

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Design, build, and maintain scalable data pipelines and ETL/ELT processes
Develop data engineering solutions using Python, SQL, and Databricks
Build and optimize data pipelines within the Databricks Lakehouse environment
Work with large, complex datasets from multiple sources
Partner with engineering teams to extract, integrate, and modernize data flows from legacy systems, including IBMi/AS400 environments
Contribute to Databricks implementation project and support data platform readiness for large scale data conversion
Design and implement change data capture (CDC) patterns
Develop and maintain data models and curate datasets for analytics, reporting, and downstream applications
Implement data quality, validation, monitoring, and error-handling processes
Optimize data pipelines and queries for performance, scalability, reliability, and cost
Partner with data architects, analysts, data scientists, application teams, and business stakeholders
Collaborate with the AI governance group to prepare and structure data for AI/ML pilot programs
Participate in the design and evolution of MMG's modern data architecture and engineering practices
Establish and promote standards for code quality, testing, documentation, version control, and deployment
Troubleshoot complex data and pipeline issues and provide sustainable solutions
Contribute to CI/CD and automated deployment practices for data engineering workloads
Mentor other engineers and contribute to the growth of MMG's data engineering capabilities

5+ years of professional experience in data engineering, software engineering, or a related technical discipline
Strong professional experience with Python
Strong experience with Databricks, including developing and optimizing data pipelines and workloads
Strong SQL skills and experience working with relational and/or analytical databases
Experience designing and implementing ETL/ELT pipelines and data integration solutions
Experience working with cloud-based data platforms and modern data architectures (Azure preferred)
Strong understanding of data modeling, data warehousing, and data lake/lakehouse concepts including medallion / multi-hop architectures
Experience with Git and modern software development practices
Experience with automated testing, deployment, and CI/CD practices
Experience establishing version control, testing, review and deployment automation for data
Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent professional experience

Experience working in the insurance or financial services industry
Experience integrating data from legacy systems, particularly IBMi/AS400 environments
Experience with Azure AI Foundry or similar AI/ML platform tooling
Experience with Apache Spark / PySpark
Experience with Databricks SQL and Delta Lake
Experience with data orchestration tools such as Azure Data Factory, Airflow, or similar technologies
Experience with APIs and event-driven or real-time data integration
Experience implementing change data capture (CDC) patterns for enterprise data integration
Experience with insurance policy administration platform data or large-scale platform data conversions
Experience with data governance, metadata, lineage, and data quality frameworks
Experience working with enterprise data warehouses and dimensional modeling
Experience with Infrastructure as Code and cloud automation
Experience using AI-assisted development tools to improve engineering productivity

Skills