Data Engineer Jobs

About The Position

Requirements

• Bachelor’s degree in Computer Science, Mathematics, Physics, Engineering, or equivalent experience.
• At least 5 years of data engineering experience, including production ELT pipelines on a cloud data platform.
• Hands-on Databricks experience with Spark, Delta Lake, orchestration, and Unity Catalog; Azure experience is preferred.
• Experience building framework-based ingestion within a medallion architecture.
• Advanced Python, including PySpark and automated testing, and advanced SQL.
• Strong data modeling skills across dimensional, normalized, and lakehouse patterns.
• Practical data governance experience, including profiling, data quality, MDM, catalog, and lineage.
• Experience with Git and CI/CD for data assets.
• Strong problem-solving skills, with a focus on root cause rather than quick fixes.
• Clear communication with technical and non-technical partners.
• A standards-first mindset that favors reusable frameworks and automation.

Nice To Haves

• At least 2 years of Consumer Packaged Goods analytics experience.
• Broader Azure stack experience, including ADLS, Data Factory, Fabric, or Power BI; Databricks certification.
• Experience with governance or catalog tools such as Purview, Collibra, Alation, or Informatica.
• Experience with streaming technologies such as Kafka or Structured Streaming, and infrastructure as code.
• Experience preparing data for machine learning or generative AI applications.
• Experience on agile teams distributed across geographies.

Responsibilities

• Build reusable, metadata-driven ingestion frameworks and batch and streaming ELT pipelines that move data through Bronze, Silver, and Gold layers, with quality gates, incremental/CDC processing, and restartable, idempotent design.
• Design dimensional, normalized, and data vault models, and build curated Gold data products with conformed dimensions that reconcile across regions and source systems.
• Profile data sources; implement automated data quality and reconciliation controls; and support master and reference data management.
• Maintain the semantic layer, catalog, lineage, and business glossary with data stewards; extend classification, masking, and access controls to AI use cases.
• Develop on Databricks using PySpark, Spark SQL, Delta Lake, Delta Live Tables, Workflows, and Unity Catalog; optimize performance and cost and contribute to disaster recovery planning.
• Write tested, production-grade Python and SQL using Git, peer review, and CI/CD, with configuration managed as code.
• Prepare AI-ready data, including feature tables, training datasets, and RAG content such as chunking, embeddings, and vector indexes.
• Publish governed data to operational systems through APIs, events, and reverse ETL, using versioned interface contracts.
• Support production operations, including monitoring, root cause analysis, and service levels; maintain documentation and runbooks for handoff to managed services.

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• Basic life insurance
• Paid vacation and sick time
• Paid Parental Leave
• Paid holidays and floating holidays
• 401(k) retirement plan with company match and profit-sharing
• Discounted Employee Stock Purchase Plan
• Eligible dependents may access applicable benefits
• Bonus eligibility