Sr Data Engineer I

Spectrum Asset Management, Inc. is seeking a Senior Data Engineer I to join their Retirement Modernization Data Enablement team. In this role, you will design and deliver data pipelines and data products, ensuring critical transactional data is trusted, well-governed, and optimized for analytics at scale.

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

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
• 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