Data Engineer

Church & Dwight is seeking a Data Engineer to join its Analytics Engineering Group. The role will support a Databricks-based lakehouse, building ingestion frameworks, ELT pipelines, governed data models, and AI-ready curated data products.

What You’ll Do

• Build reusable, metadata-driven ingestion frameworks and batch and streaming ELT pipelines that move data through Bronze, Silver, and Gold layers using defined quality gates, incremental and CDC processing, and restartable, idempotent design.
• Create dimensional, normalized, and data vault models, and deliver 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, and extend classification, masking, and access controls for AI use cases.
• Develop on Databricks using PySpark, Spark SQL, Delta Lake, Delta Live Tables, Workflows, and Unity Catalog, optimizing performance and cost and contributing 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 (chunking, embeddings, vector indexes).
• Publish governed data to operational systems via APIs, events, and reverse ETL, using versioned interface contracts.
• Support production operations including monitoring, root cause analysis, and service level expectations, and maintain documentation and runbooks for handoff to managed services.

Required Qualifications

• Bachelor’s degree in Computer Science, Mathematics, Physics, Engineering, or equivalent experience.
• 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, preferably on Azure.
• Experience building framework-based ingestion within a medallion architecture.
• Advanced Python (including PySpark and automated testing) and 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.

Preferred Qualifications

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

Tools and Technologies

Databricks, PySpark, Spark SQL, Delta Lake, Delta Live Tables, Workflows, Unity Catalog, Python, Git, CI/CD, APIs, Kafka, Structured Streaming, Azure, ADLS, Data Factory, Fabric, Power BI, Purview, Collibra, Alation, Informatica, Infrastructure as code, Reverse ETL.

Compensation

USD 92,500 - 131,700 per year.

Work Location and Schedule

Hybrid in Ewing, NJ. In-person attendance is required on Tuesdays, Wednesdays, and Thursdays, with remote work options on Mondays and Fridays.

Benefits

• Medical, dental, and vision
• Basic life insurance
• Paid vacation and sick time
• Paid Parental Leave
• Paid holidays and floating holidays
• 401k retirement plan (with company match and profit-sharing)
• Discounted Employee Stock Purchase Plan