Senior Data Engineer

MMG Insurance•,

8d•$115,000 - $146,000•Hybrid

About The Position

MMG Insurance is seeking a Senior Data Engineer to help build, modernize, and maintain the data platforms that support business intelligence, analytics, reporting, and data-driven decision-making across the organization. This role requires consistent travel to our Portsmouth, NH office. Candidates will need to be able to travel to the office in New Hampshire at minimum, monthly. This role is open to candidates residing in ME/NH/MA. This role will be responsible for designing and developing scalable data pipelines and solutions using modern cloud data technologies, with a strong focus on Python, Databricks, SQL, and data engineering best practices. The ideal candidate is a hands-on engineer who can work across teams to understand business needs, translate them into reliable data solutions, and help advance MMG's data engineering capabilities, including modernizing how our legacy IBMi systems connect into the broader data ecosystem. This role will also play a key part in preparing our data platform for data conversion readiness. This is a modernization role as much as a build role. MMG's data estate spans a modern Databricks lakehouse, an established enterprise reporting layer, and legacy ETL and warehouse processes that have grown up over many years. You will help move that estate onto a governed, version-controlled, automated foundation, designing what replaces the manual processes, not only maintaining what exists today.

Requirements

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.
5+ years of professional experience in data engineering, software engineering, or a related technical discipline.
Strong professional experience with Python and the ability to write clean, maintainable, production-quality code.
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.
Strong analytical and problem-solving skills.
Ability to communicate effectively with both technical and non-technical stakeholders.

Nice To Haves

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.

Responsibilities

Design, build, and maintain scalable, reliable 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, including enterprise applications, databases, APIs, and other data platforms.
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, including data mapping, migration, and integration work.
Design and implement change data capture (CDC) patterns to support real-time and incremental data integration.
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 to deliver high-quality data solutions.
Collaborate with the AI governance group to prepare and structure data for AI/ML pilot programs, including initiatives built on Azure AI Foundry.
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.