Senior Data Engineer

At Plymouth Rock, a fast-growing, analytics-driven insurer, we believe data engineering can redefine how insurance operates. As the Senior Data Engineer on our Enterprise Data team, you will be at the heart of this transformation. This high-visibility role is critical to our mission-empowering a team of top-tier data scientists to generate breakthrough insights that drive profitable growth, operational excellence, and competitive advantage.

You will architect and manage the data pipelines that connect internal systems, third-party sources, and advanced analytical platforms, directly enabling our most strategic research initiatives. Working collaboratively across Data Science, IT, and business units, you will help shape how Plymouth Rock leverages cloud platforms, machine learning infrastructure, and modern data engineering to power enterprise-wide innovation. This is a unique opportunity to be both a builder and a thought leader in a hands‑on role at the forefront of applied data science in the insurance industry.
Responsibilities

• Serve as the hands‑on leader of data engineering for the Enterprise Advanced Analytics team-designing, building, and optimizing data pipelines and workflows to empower advanced research and analytics.
• Collaborate with key leaders across Data Science, IT and Business to automate and empower data and machine learning automation across our Personal Auto and Homeowner insurance business units.
• Partner with IT on the transition to a cloud‑based AWS data lake-championing new architectures and ways of working that harness cutting‑edge technologies and unlock new analytical capabilities.
• Create and manage data infrastructure to design, develop, and enhance data and analytics solutions and pipelines, enabling data‑driven decision‑making processes.
• Design and implement automated pipelines for data and machine learning workflows and infrastructure with testing, versioning, and rollback capabilities.
• Designing and building reusable processes and templates for packaging, testing, and deployment of internal python libraries, containers and data pipelines and machine learning workflows.
• Stay current with industry trends and best practices in data and machine learning engineering and recommend improvements to existing processes.
• Play a pivotal role in shaping the future of Plymouth Rock's data science and advanced analytics strategy while growing your career in a dynamic, innovation‑driven environment.

• A vision of how to do things differently - better, faster, cheaper, adding more value - than our competitors.
• A master's degree in computer science, Information Systems or related field.
• 5+ years of related data/data platform or machine learning engineering experience with a focus on designing, building, and deploying automated pipelines and workflows.
• Experience in building automated deployment pipelines and CI/CD workflows using Jenkins, Git Hub Actions, Terraform, Cloud Formation or similar tools.
• Experience automating workflows using AWS cloud services (Lambdas, ECS, S3, Step Functions, Event bridge etc)
• Experience with Docker, Padman and other containerization tools
• Expert in Python, proficient in SQL, additional R and SAS knowledge and a bonus for legacy code.
• Experience with data modeling and data warehousing.
• Experience with cloud data platforms, Snowflake (preferable), AWS.
• A design thinking and test‑driven development mindset.
• Experience with business intelligence tools and reporting solutions (Tableau etc.).
• Knowledge of python packaging and distribution tools such as pip, poetry, setup tools, twine, etc.
• Knowledge of data engineering and machine learning concepts, ETL/ELT, data lakes, data quality metrics
• Strong communication and collaboration skills, with a track record of working effectively across technical and business teams.
• Curiosity and commitment to continuous learning in emerging data engineering tools, platforms, and best practices.