Principal Data Engineer, Global Liquid Markets-Public Markets and Research

Liberty Mutual; Boston (MA); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Liberty Mutual Investments Technology seeks a Principal Data Engineer to advance our cloud-native data platform for Global Liquid Markets. You will design and operate scalable data pipelines, harness AI tools, and mentor squads across four teams to deliver trusted data for investment insights and decision-making.

In this hybrid Boston-based role, you will push for high-quality data products, collaborate with product owners, and shape the data roadmap while ensuring strong governance and security

Qualifications

• 8+ years of data engineering experience in production
• Expert SQL and data modeling
• Proficient in Python for data workflows
• CI/CD experience in data pipelines
• Experience with Snowflake and AWS
• Experience using AI tools to improve speed and quality
• Experience with data quality and testing tools like dbt/iceDQ

Responsibilities

• Lead data engineering across four full-stack squads while staying hands-on
• Design and run automated, high-performance data pipelines on Snowflake and AWS
• Shape data products and scalable models for analytics and AI-enabled applications
• Own testing strategy, unit and regression tests, and quality standards
• Drive AI-powered data engineering to automate repetitive tasks with guardrails
• Translate business needs into a prioritized data roadmap with product owners
• Mentor engineers, conduct code reviews, and set technical direction

Skills

8+ years data engineering

Python proficiency

SQL expert

CI/CD experience

Data modeling

Education

Bachelor's degree in technical or business field

Tools

Snowflake

AWS

dbt

iceDQ

GitHub Actions

Job description

Principal Data Engineer, Global Liquid Markets-Public Markets and Research

Are you passionate about data and excited to shape the future of investing through innovative technology, including Agentic AI? Do you thrive in an inclusive, collaborative environment where your ideas are valued? Are you curious, adaptable, and eager to learn, experiment, and apply AI to solve real problems? If so, come build with us at Liberty Mutual Investments.

At Liberty Mutual Investments (LMI), we manage a high-quality investment portfolio using a disciplined strategy. LMI operates as a complete investment firm within our Fortune 100 company. Our investment professionals are critical to helping us keep our promises to policyholders, claimants, and their families.

NOTE: This role will have a hybrid work arrangement (2x/week) in our Boston, MA office.

Job Description

At Liberty Mutual Investments Technology, we are seeking a skilled Principal Data Engineer who is ready to take on exciting challenges, help shape our cloud-native, data platform, and make a real impact across our investment insights. You will build modern, AI powered solutions and robust data pipelines that power insights across our Global Liquid Markets (Public Markets and Research) investment portfolio, and you will use AI and agentic tools to build faster, test smarter, and automate the work that slows teams down. This is a high-impact opportunity to grow your career in a supportive, growth-oriented team working on meaningful challenges.

Key Responsibilities

• Lead data engineering across four full stack squads, driving data design, best practices, and technical decisions while staying hands-on within one.
• Build data people can trust: Design and run automated, high-performance data pipelines on Snowflake and AWS that bring market and vendor data into the platform reliably and at scale.
• Shape the data products : Design the data models behind scalable products that power analytics and applications used in real investment decisions with an AI first mindset.
• Make quality a standard, not an afterthought: Own the testing strategy, from unit tests built into the pipeline to independent regression testing and set shared quality standards with Core Data and data governance.
• Drive AI-powered data engineering: Use AI to speed up how the squads build, test, and operate data pipelines, and apply agentic AI to automate repetitive engineering work, with sound guardrails and human review.
• Turn business needs into a roadmap : Partner with product owners and tech leads to translating what the business needs into a clear, prioritized data roadmap.
• Raise the engineering bar: Mentor engineers, lead code reviews, and model the practices you want the squads to follow.

Qualifications

• Bachelor's degree in a technical or business field, or equivalent hands-on experience.
• 8+ years in data engineering, with a proven record of delivering scalable, high-performing data pipelines and architecture in production.
• Experience using AI tools to improve the speed, quality, and scale of work; can point to concrete workflows where AI adds value; critically evaluates and validates AI-generated output; and applies AI responsibly, protecting confidential and customer data.
• Experience with institutional investment or asset management data, ideally in public markets (fixed income, and derivatives) and research (data driven insights from structured and unstructured company, sector, macro sources).
• Expert SQL, with a strong command of data modeling, warehousing, and architecture, and sound judgment on design tradeoffs.
• Expert-level experience in designing and architecting scalable, high-performance Snowflake and AWS data solutions, including complex data models, ETL/ELT pipelines, performance optimization, and establishing best practices for data engineering across multiple squads
• Proficient in Python for transforming, integrating, and automating data workflows.
• Hands-on experience with AWS services used in data and application workloads, such as S3, Lambda, RDS (PostgreSQL), API Gateway, and IAM.
• Hands-on CI/CD experience, automating how data work is built, tested, and deployed with tools such as GitHub Actions or similar.
• Experience building data quality and automated testing into pipelines, from tests that run with every change to regression checks that confirm data products stay correct after releases, using data testing and quality tools such as dbt, iceDQ, or similar.
• Experience leading technical work, such as guiding design decisions, mentoring engineers, or setting a team's technical direction.

About Us

Pay Philosophy: The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employe