Senior Data Engineer

MMG Insurance; Portsmouth (NH); On-site; USD 115,000 - 146,000; Full time

Job summary

MMG Insurance seeks a Senior Data Engineer to design, build, and modernize data platforms supporting BI, analytics, and reporting across the organization. You will craft scalable data pipelines using Python, Databricks, SQL, and modern data engineering practices.

The role requires travel to Portsmouth, NH monthly, with flexibility for candidates in ME/NH/MA. You will collaborate with engineering, analytics, and AI teams to enable data conversion, governance, and AI pilot readiness in a governed

Qualifications

• 5+ years of professional experience in data engineering or related technical discipline.
• Strong Python and production-quality code experience.
• Strong Databricks experience with data pipelines/workloads.
• Strong SQL skills and experience with relational/analytical databases.
• Experience designing ETL/ELT pipelines and data integration solutions.
• Experience with cloud-based data platforms and modern data architectures (Azure preferred).
• Experience with Git, automated testing, deployment, and CI/CD practices.

Responsibilities

• 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.
• Collaborate with engineering teams to modernize data flows from legacy systems (IBMi/AS400).
• Support data platform readiness for large-scale data conversion and integration.

Skills

Python

Databricks

SQL

ETL/ELT

Data Modeling

Git

CI/CD

Communication

Education

Bachelor's degree in Computer Science, Information Systems, Engineering, or related field

Tools

Databricks

PySpark

Delta Lake

Azure Data Factory

Airflow

Job description

Job Description

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.

Key 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.

Required Qualifications

• 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.

Preferred Qualifications

• 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 dataor 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.

What Success Looks Like

• Build reliable, scalable, and maintainable data pipelines that the organization can trust.
• Help expand MMG's use of Databricks and modern data engineering practices.
• Improve the availability, quality, and usability of enterprise data.
• Replace manual and repetitive data processes with automated, monitored pipelines, reducing the operational effort spent correcting and reconciling data by hand.
• Deliver data solutions that meet both technical requirements and business needs.
• Help establish consistent engineering standards across the data organization.
• Serve as a technical leader and mentor for other data engineers.

Core Technologies

Required: Python | Databricks | SQL | ETL/ELT | Data Modeling | Git | Cloud Data Platforms

Preferred: PySpark | Delta Lake | Azure | Azure Data Factory | Azure AI Foundry | Databricks SQL | CI/CD | APIs | CDC | Data Governance

Compensation Range

The anticipated annual compensation range for this position is $115k-$146k. This position may be filled at different levels depending on the candidate's experience and qualifications and the final title, level, and compensation will be determined based on the selected candidate's qualifications, experience, skills, and overall fit for the role. Compensation decisions are made in alignment with internal equity and market considerations.

Why MMG Insurance

MMG Insurance is investing in modern data infrastructure and AI capabilities to support our engineering teams and business operations. This is an opportunity to shape the data foundation for emerging AI pilot programs while working on meaningful, high‑impact projects alongside a collaborative IT/engineering organization.

Essential Functions

The essential functions of this position include designing/building scalable data pipelines and cloud-based data solutions, developing/integrating data systems using modern engineering tools and collaborating with cross‑functional teams to deliver reliable, high‑quality data products while supporting data modernization initiatives. These duties require the ability to analyze, interpret and work with complex data sets, systems, and technical information and the ability to communicate and collaborate effectively with technical and non‑technical stakeholders. The position is primarily performed in an office or remote work environment and requires prolonged periods of sitting and computer use. The role involves frequent verbal and written communication, participation in virtual and in‑person meetings, and occasional travel to client or company locations. Consistent with applicable law, reasonable accommodations will be made to support individuals with disabilities in performing the essential functions of their job provided that such accommodations do not impose an undue hardship on the business. The organization will engage in an interactive accommodation process as needed.