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Data Engineer

Church & Dwight Open · verified Oct 24, 2026
USA, Ewing, NJ Full-time Mid-level Data Engineering

At a glance

Mid-level Data Engineering role at Church & Dwight. USA, Ewing, NJ · full-time · $92,500–$131,700 base.

SalaryStated by Church & Dwight
$92,500 – $131,700
Base salary for this role, in USD per year, as published in the posting.
RoleData Engineering
SeniorityMid-level
LocationUSA, Ewing, NJ
EmploymentFull-time
Base pay$92,500–$131,700
PostedOct 23, 2026 · 1d ago
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Build reusable ingestion systems and batch or streaming ELT flows, moving data through Bronze, Silver and Gold with quality checks
  • Shape dimensional, normalized and data vault models, then create Gold data products with dimensions aligned across regions and systems
  • Inspect source data and add automated checks for quality, reconciliation, master data and reference data
  • Develop and tune Databricks workloads, while maintaining the semantic layer, catalog, lineage, glossary and access controls
  • Prepare feature tables, training sets or RAG material, and handle monitoring, root-cause analysis and operational handoff guides

What you bring

  • A bachelor's degree in a listed technical field, or equivalent experience
  • At least five years building production ELT pipelines on cloud data platforms
  • Practical Databricks experience spanning Spark, Delta Lake, orchestration and Unity Catalog
  • Advanced Python, including PySpark and automated testing, plus SQL and strong data-modeling ability
  • Hands-on data governance work and experience applying Git and CI/CD to data assets

Who this fits

This mid-level role suits someone who builds reusable, governed lakehouse systems and communicates with technical and business partners. You’ll coordinate with a managed services team working across time zones. The hybrid role is based in Ewing, New Jersey, with in-person attendance Tuesday through Thursday and remote work available Monday and Friday.

From the employer

A collective energy and ambition. A place where you can make a real difference.


We’re a company that genuinely cares about our people, our products, our consumers and the environment.


Our unique, informal culture champions courage, determination and collaboration. Knowing we have an open and supportive team means each of us has the freedom to take responsibility and ownership. We have a shared passion to work hard, innovate and push boundaries.

United by the belief that when we strive for growth, anything is possible. While we might not be the largest company in our industry, we believe we can have the biggest impact because: Together We Have the Power to Win.

Role Summary


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..


About the Role


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.

Work Environment


Hybrid: This is a hybrid role based in Ewing, NJ, and requires in- person attendance on Tuesdays, Wednesdays, and Thursdays, with remote work options on Mondays and Fridays.

Role Accountabilities and Responsibilities


  • 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

Skills and Competencies


  • 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

Education and Experience


Required Qualifications

  • 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

Preferred Qualifications

  • 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

Compensation and Benefits


The U.S. base salary range for this full-time position is $92,500– $131,700. This position is also eligible for a bonus.


As a Church & Dwight US employee, you (and eligible dependents, as applicable) will have access to medical, dental, vision, basic life insurance, paid vacation and sick time, and Paid Parental Leave. U.S. employees are entitled to paid holidays, floating holidays, and vacation days starting in their first year of employment depending on hire date. You are also able to participate in our 401k retirement plan (with company match and profit-sharing) and Discounted Employee Stock Purchase Plan.  


The actual base pay offered to the successful candidate will be based on multiple factors, including, but not limited to, job-related knowledge/skills, experience, business needs, geographical location, and internal pay parity.  Compensation decisions are dependent upon the facts and circumstances of each position and candidate.


Church & Dwight is proud to be an Equal Opportunity Employer/Veterans/Individuals with Disabilities.

For more information on our company, our brands and our culture visit us at http://www.churchdwight.com/

Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Engineering$90k+

Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.