Data Engineer

Liberty Mutual Insurance•Boston, MA

17d•Hybrid

About The Position

Join USRM Data Analytics & Engineering at Liberty Mutual as a Data Engineer. You’ll build and operate cloud data platforms that deliver premium, loss, and exposure data used for regulatory reporting, actuarial models, and business decisions. You’ll work on a distributed Agile team and use Snowflake, Informatica IDMC, SQL, Python, AWS, and modern DevOps and AI-assisted tooling. This is a hybrid role requiring two days in the office a week in one of the following locations: Boston, Portsmouth, Plano, Indianapolis, or Columbus You must be authorized to work in the United States without employer sponsorship now or in the future. We will not sponsor employment visas. Candidates who will require future sponsorship, including candidates on CPT/OPT/STEMOPT who will require future sponsorship, are not eligible to apply. Under general supervision, responsible for the analysis, development, and execution of data solutions of moderate complexity to manage the information lifecycle needs of an organization. Collects, integrates and analyzes organizational data with the purpose of drawing conclusions from that information. Develops, constructs, tests, and maintains data architectures for data platforms, database, analytical/reporting, or data science systems. Establishes and builds data systems including providing standards, policies, practice, procedures, governance and quality assurance for data deliverables. Recommends methods to improve data reliability, quality, and efficiency.

Requirements

Bachelor’s or Master’s degree in a technical or business field, or equivalent experience.
Generally 3 years of professional experience building data pipelines or data platforms.
Hands-on experience with Snowflake and Informatica IDMC or similar ETL/ELT tools.
Strong SQL skills and experience with Python.
Practical experience with AWS data services (S3, Glue, etc.).
Experience with automated testing, CI/CD, and data pipeline orchestration (e.g., Control‑M, Airflow).
Experience working on Agile teams and collaborating with analytics/business stakeholders.

Nice To Haves

Experience designing cloud or hybrid data architectures and data modeling for analytics.
Background in data warehousing, reporting, or regulatory reporting (insurance domain helpful).
Experience with mainframe data sources or legacy ingestion (a plus).
Familiarity or interest in AI-assisted development tools and observability platforms.
Experience mentoring others or owning end-to-end features in production.

Responsibilities

Design and develop low to moderately complex programs and tools to support ingestion, curation and provisioning of enterprise data to achieve analytics or reporting.
Builds and designs data models and data architecture of low to moderate complexity that improve accessibility, efficiency, governance and quality of data.
Make recommendations for how to improve data.
Provides successful deployment and provisioning of data solutions to production or other required environments.
Identify possible process improvements that address technology gaps within a single business process of moderate complexity.
Builds proficient knowledge of technology enablers.
Analyzes and prepare moderate to complex technology enabled recommendations to address gaps within a single business process.
Performs other duties and projects assigned.
Design, develop, and maintain ETL/ELT pipelines using Snowflake and Informatica IDMC.
Build and optimize data models, views, and tables for analytics and reporting.
Write, review, and optimize SQL and Python for data processing and integrations.
Manage data storage and movement using AWS (S3 and related services).
Implement automated testing (unit, integration, regression) for pipelines and support test tooling.
Improve CI/CD, deployment automation, orchestration (e.g., Control-M) and monitor data workflows.
Troubleshoot data issues, perform RCA, and implement long-term fixes.
Produce technical documentation, data lineage, and support data governance and quality initiatives.
Participate in sprint planning, code reviews, and mentoring of junior engineers.