Sr Data Engineer I

Principal Financial Group•Raleigh, NC

1d•Hybrid

About The Position

We’re looking for a Senior Data Engineer I to join our Retirement Modernization Data Enablement team. In this role, you'll help enable how critical transactional data moves from source systems into enterprise analytics platforms, ensuring the data is trusted, well-governed, and optimized for insight at scale. You'll design and deliver data pipelines and data products, working across teams to support analytics, reporting, and emerging data use cases while contributing to engineering standards and best practices in a modern data ecosystem. You’ll have the opportunity to Design, build, and maintain scalable data pipelines and systems across multiple platforms supporting the full data lifecycle, from ingestion and transformation to analytics-ready datasets Deliver high-quality, reliable data solutions by applying best practices in version control, testing, monitoring, and proactively addressing data quality issues, performance bottlenecks, and technical debt Partner with upstream and downstream teams and contribute to technical design discussions to ensure data is effectively modeled, governed, and delivered Apply security policies and standards during development and support risk mitigation efforts Create and maintain documentation while collaborating with team members through code reviews, pairing, and knowledge sharing As Principal continues to modernize its systems, this role will offer you an exciting opportunity to build solutions that will directly impact our long-term strategy and tech stack, all while ensuring that our products are robust, scalable, and secure! Operating at the intersection of financial services and technology, Principal builds financial tools that help our customers live better lives. We take pride in being a purpose-led firm, motivated by our mission to make financial security accessible to all. Our mission, integrity, and customer focus have made us a trusted leader for more than 140 years.

Requirements

Bachelor's degree plus 6+ years related work experience or a Master's in related field plus 2+ years related work experience
Proven experience delivering data engineering solutions, including data ingestion, transformation, modeling, and storage to support analytics, reporting, and advanced data use cases, with exposure to data mesh principles in modern data platform environments
Demonstrated ability to shape data architecture and influence technical strategy across teams, establishing patterns, standards, and best practices
Trusted technical leader with strong communication and collaboration skills who can influence across teams and business units and navigate ambiguity in modernizing data environments
Experience elevating the people around you; coaching, mentoring, and helping others grow through thoughtful feedback and knowledge sharing
Proven experience working across the full data lifecycle, from source‑aligned ingestion and foundational data preparation through to analytics‑ready datasets, with an understanding of how upstream design decisions enable downstream analytics and data products
Strong technical foundation working hands‑on with data and data stores, including SQL, and with data pipeline development
Experience optimizing data pipelines and processing systems for high‑volume, complex datasets
Experience implementing data quality management across the data lifecycle, including validation, reconciliation, and mastering, with an emphasis on observability, monitoring, and operational readiness

Nice To Haves

Experience with modern enterprise data platforms (e.g., Snowflake)
Familiarity with data quality tools and practices (e.g., Ataccama)
Experience with data integration tools (e.g., AWS Glue, Fivetran, Informatica IDMC)
Experience with transactional/source system data modeling (e.g., 3NF)
Experience with monitoring, observability, and pipeline reliability

Responsibilities

Design, build, and maintain scalable data pipelines and systems across multiple platforms supporting the full data lifecycle, from ingestion and transformation to analytics-ready datasets
Deliver high-quality, reliable data solutions by applying best practices in version control, testing, monitoring, and proactively addressing data quality issues, performance bottlenecks, and technical debt
Partner with upstream and downstream teams and contribute to technical design discussions to ensure data is effectively modeled, governed, and delivered
Apply security policies and standards during development and support risk mitigation efforts
Create and maintain documentation while collaborating with team members through code reviews, pairing, and knowledge sharing