Data Engineer
Location: Bellevue
Department: AI Enablement Engineering
Location Type: IN_OFFICE
Employment Type: FULL_TIME
About the Role
What You'll do
- Own the data lifecycle end-to-end, from ingestion to production-ready ontology
- Ingest data from databases, streams, batch files, and incremental feeds
- Design and operate medallion-style lakehouse pipelines (bronze → silver → gold)
- Transform raw inputs into a consistent digital twin of supply chain reality
- Serve high-quality data to analytics, AI workflows, and write-back systems
- Own data correctness and reliability in production, including monitoring, on-call, and incident response
- Build data quality checks, validations, and safe backfill strategies
- Use AI-assisted tools responsibly, reviewing and hardening generated code
- Reduce complexity by simplifying pipelines and automating repetitive work
What You Bring
- Degree in Computer Science, Mathematics, Statistics, or other data-intensive discipline with substantive engineering experience
- 2+ years demonstrated development experience using SQL, Scala, Spark, Flink, Beam, and/or Python
- 2+ years demonstrated experience in data management (structured and unstructured) and modern database technologies
- Experience building and operating production data pipelines in distributed systems
- Hands-on experience with lakehouse or warehouse architectures
- Strong schema design skills for structured and semi-structured data
- A production mindset—you’ve owned systems that break and fixed them
- Experience supporting AI/ML or AI-powered products
- Familiarity with streaming or incremental processing
- Experience with data quality, observability, or anomaly detection
- A deep curiosity and eagerness to problem solve without a playbook. If you require intense structure and process, this is not the place for you
- Ability to work collaboratively through ambiguity, with urgency, patience, and good humor
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