Data Engineer

ColgatePiscataway, NJ
Hybrid

About The Position

We are seeking a passionate and detail-oriented Data Engineer to join our Digital Tech & Data team. In this role, you will be responsible for building and maintaining the data pipelines that support our digital ecosystem — from ingesting raw data across multiple digital touchpoints to delivering clean, robust data that business teams can trust and act on. You will bring engineering rigour to data — treating pipelines, models, and infrastructure as production-grade software — while staying closely connected to the digital business context your work enables.

Requirements

  • Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related discipline.
  • 2–3 years of hands-on experience in a data engineering or analytics engineering role, ideally within a digital or e-commerce environment.

Nice To Haves

  • Proven experience building and maintaining production-grade data pipelines using Apache Airflow.
  • Strong working knowledge of Snowflake, including data modelling, performance tuning, clustering, and warehouse cost management.
  • Demonstrated experience developing dbt projects — writing modular, tested, and well-documented transformation logic.
  • Practical experience using Terraform to provision and manage cloud data infrastructure in a repeatable, version-controlled manner.
  • Proficiency in Python for writing data pipelines, custom operators, and utility tooling.
  • Strong SQL skills with the ability to write and optimise complex queries across large datasets.
  • Fluency in driving an AI coding tool across pipeline codebase: scoping changes, providing the right files as context.

Responsibilities

  • Design, build, and maintain production-grade data pipelines in Airflow that ingest data from digital touchpoints into Snowflake.
  • Develop modular, tested, and well-documented dbt models that transform raw data into reliable, business-ready datasets — owning the full lifecycle from source definition to exposure.
  • Provision and manage cloud data infrastructure (Snowflake objects, Airflow environments, supporting GCP resources) through Terraform, with everything version-controlled and peer-reviewed.
  • Implement and uphold data quality, observability, and testing standards across pipelines
  • Tune Snowflake performance and manage warehouse cost — clustering, query profiling, resource monitors and treat cost as a first-class engineering concern.
  • Implement pipelines to platform standards — branching strategy, CI/CD for dbt and Airflow, code review norms, documentation, naming conventions

Benefits

  • medical
  • dental
  • vision
  • basic life insurance
  • paid parental leave
  • disability coverage
  • participation in the 401(k) retirement plan with company matching contributions subject to eligibility requirements
  • a minimum of 15 vacation/PTO days
  • 13 paid holidays
  • Paid sick leave
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