Principal Data Engineer
Madison, WIAll locationsMadison, WIUnited States > Madison : 1 Exact Lane On-site
$129,300–$258,700 a yearJobFig found this opening at its original source and checks that it remains available.
About the role
The Principal Data Engineer (IC) is a senior individual contributor and the accountable technical leader for assigned cross-domain initiatives and enterprise data engineering capabilities. The role owns integrated technical direction and technical outcomes for work spanning multiple data domains, defines and stewards enterprise engineering standards and reference architectures, and drives convergence where duplicated or inconsistent solutions create enterprise cost, risk, or operational burden. The role advises on scope, sequencing, capacity, dependencies, and technical debt, but does not independently commit domain resources or business delivery dates. This position has no people-management responsibility. Enterprise Data operates a domain-aligned model built on Databricks and Unity Catalog. Working with Domain Leaders, Staff Engineers, Platform Engineering, and partner organizations, the role converts ambiguous enterprise needs into executable architecture and carries the most complex or highest-risk work through validation and production. The role remains hands-on through prototyping, reference implementations, critical-path development, design and code review, and production problem solving. This role is based in Madison, WI. Relocation assistance may be available for qualified candidates.
What you'll bring
- Ability to work nights and/or weekends, as needed.
- Bachelor's Degree in Data Science, Computer Science, Information Systems, Mathematics, or Engineering.
- Expert-level experience with software development design and development and with relevant domain specific skills (see below).
- Spark on Databricks or comparable platforms
- Python, Scala, SQL, and Snowflake experience.
- ETL and ELT data pipelines, including batch and event-driven patterns.
- Designing and implementing data modeling solutions using relational, dimensional, and/or NoSQL databases.
- Database architecture testing methodology, including execution of test plans, debugging, and testing scripts and tools.
- Open data file and table formats (Parquet, Avro, Delta Lake)
- cloud infrastructure and delivery services (AWS, S3, SQS, and GitLab CI/CD).
- REST API development
- familiarity with BI concepts and Tableau performance considerations.