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# Data Engineer

- **Company:** Church & Dwight
- **Location:** Ewing Township, NJ, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $92,500.0 - $131,700.0
- **Contract:** Permanent contract
- **Skills:** Training Data, Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Application Frameworks, Automation of Tests, Microsoft Azure, Profiling, Continuous Integration, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Vault Modeling, Digital Assets, Disaster Recovery, Apache Hive, Python (Programming Language), Reference Data, Power BI, Azure Active Directory, Standard Sql, Runbook, SQL Databases, Data Streaming, Cloud Platform System, Retrieval-Augmented Generation, Apache Spark, Generative AI, Git, Data Lakes, Pyspark, Information Technology, Collibra, Apache Kafka, Operational Systems, Data Management, Data Pipelines, Databricks
- **Published:** October 26, 2026
- **Apply:** https://churchdwight.wd1.myworkdayjobs.com/chdcareers/job/USA-Ewing-NJ/Data-Engineer_R2026-15824

## About the Role

* Strong problem-solving skills, with a focus on root cause over quick fixes

 * Clear communication with both technical and non-technical partners
 * A standards-first mindset that favors reusable frameworks and automation, * Bachelor's degree in Computer Science, Mathematics, Physics, Engineering, or equivalent experience required
 * 5 + years of data engineering experience, including production ELT pipelines on a cloud data platform required
 * Hands-on Databricks experience (Spark, Delta Lake, orchestration, 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: profiling, data quality, MDM, catalog, and lineage
 * Experience with Git and CI/CD for data assets, * 2+ years of Consumer Packaged Goods analytics experience preferred
 * Broader Azure stack experience (ADLS, Data Factory, Fabric, Power BI); Databricks certification
 * Governance or catalog tools such as Purview, Collibra, Alation, or Informatica
 * Streaming (Kafka, Structured Streaming) and infrastructure as code
 * Experience preparing data for ML or generative AI applications
 * Experience on agile teams distributed across geographies

## Description

Church & Dwight is seeking a Data Engineer to join our team. As a member of the Analytics Engineering Group, the Data Engineer builds and maintains the ingestion frameworks, ELT pipelines, data models, and curated data products that deliver insight to CHD business functions worldwide.., The role centers on a Databricks lakehouse built on a Bronze/Silver/Gold medallion architecture, with an emphasis on reusable, metadata-driven engineering, strong governance, and AI-ready data.

The Data Engineer will partner closely with analytics engineers, architects, data scientists, data stewards, and business analysts, and work across time zones with a global managed services team., * Build reusable, metadata-driven ingestion frameworks and batch/streaming ELT pipelines that promote data through Bronze, Silver, and Gold with defined 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 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 (PySpark, Spark SQL, Delta Lake, Delta Live Tables, Workflows, 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 data sets, and RAG content (chunking, embeddings, vector indexes)
 * Publish governed data to operational systems through APIs, events, and reverse ETL, with versioned interface contracts
 * Support production operations (monitoring, root cause analysis, service levels) and maintain documentation and runbooks for handoff to managed services