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Data Engineer

Piscataway, NJ, US

Pay
USD 96,800–137,000/yearAnnual period assumed · Location-specific pay — pay source
Fluency in driving an AI coding tool across pipeline codebase: scoping changes, providing the right files as context. Compensation and Benefits Salary Range $96,800.00 - $137,000.00 USD Pay is determined based on experience, qualifications, and location. Salaried employees may also be eligible for discretionary bonuses, profit-sharing, and long-term incentives for Executive-level roles.
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Work setup
Unconfirmed
Employment
Unconfirmed
Apply at Colgate-Palmolive

What you’ll work on

Full posting

We are seeking a passionate and detail-oriented Data Engineer to join our Digital Tech & Data team.

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.

  • Design, build, and maintain production-grade data pipelines in Airflow that ingest data from digital touchpoints into Snowflake.

  • Implement and uphold data quality, observability, and testing standards across pipelines

  • Implement pipelines to platform standards — branching strategy, CI/CD for dbt and Airflow, code review norms, documentation, naming conventions

From the employer’s posting
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.
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.
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 Required Qualifications:

What you’ll bring

All qualifications

Core experience

  • 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.

Preferred experience

  • Proven experience building and maintaining production-grade data pipelines using Apache Airflow.
  • 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.
Qualification wording
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.
Proven experience building and maintaining production-grade data pipelines using Apache Airflow.
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.

Tools in this posting

  • Python
  • SQL
  • dbt
  • Google Cloud (GCP)
  • Snowflake
  • Terraform
  • Airflow
Source — Tool mentions in context
- 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.
- 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.
- 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.
- 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 Required Qualifications:
- 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.
- 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
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.
- 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
- 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.
- 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.
Preferred Qualifications: - 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.

About Colgate-Palmolive

Colgate-Palmolive Company is a global consumer products company operating in over 200 countries specializing in Oral Care, Personal Care, Home Care, Skin Care, and Pet Nutrition.

In the employer’s words · Read in context

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May 28, 2026 · 140d ago
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Last seen by us
Oct 15, 2026

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Job description

View original posting ↗

No Relocation Assistance Offered
Job Number #173490 - Piscataway, New Jersey, United States

Who We Are

Colgate-Palmolive Company is a global consumer products company operating in over 200 countries specializing in Oral Care, Personal Care, Home Care, Skin Care, and Pet Nutrition. Our products are trusted in more households than any other brand in the world, making us a household name!

Join Colgate-Palmolive, a caring, innovative growth company reimagining a healthier future for people, their pets, and our planet. Guided by our core values—Caring, Inclusive, and Courageous—we foster a culture that inspires our people to achieve common goals. Together, let's build a brighter, healthier future for all.

 

Role Summary: 

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.

 

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

Required Qualifications:

Education: 

  • Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related discipline.

Experience: 

  • 2–3 years of hands-on experience in a data engineering or analytics engineering role, ideally within a digital or e-commerce environment.

 

Preferred Qualifications:

  • 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.


Compensation and Benefits
Salary Range $96,800.00 - $137,000.00 USD

Pay is determined based on experience, qualifications, and location. Salaried employees may also be eligible for discretionary bonuses, profit-sharing, and long-term incentives for Executive-level roles.

Benefits: Salaried employees enjoy a comprehensive benefits package, including medical, dental, vision, basic life insurance, paid parental leave, disability coverage, and participation in the 401(k) retirement plan with company matching contributions subject to eligibility requirements. Additional benefits include a minimum of 15 vacation/PTO days (hourly employees receive a minimum of 120 hours) and 13 paid holidays (vacation days are prorated based on the employee's hire date within the calendar year). Paid sick leave is adjusted based on role and location in accordance with local laws. Detailed information regarding paid sick leave entitlements will be provided to employees upon hiring and may be subject to adjustments based on changes in legislation or company policies.

Our Commitment to Inclusion
Our journey begins with our people—developing strong talent with diverse backgrounds and perspectives  to best serve our consumers around the world and fostering an inclusive environment where everyone feels a true sense of belonging. We are dedicated to ensuring that each individual can be their authentic self, is treated with respect, and is empowered by leadership to contribute meaningfully to our business.

Equal Opportunity Employer
Colgate is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, ethnicity, age, disability, marital status, veteran status (United States positions), or any other characteristic protected by law.

Reasonable accommodation during the application process is available for persons with disabilities. Please complete this request form should you require accommodation.

For additional Colgate terms and conditions, please click here.

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Pay
Fluency in driving an AI coding tool across pipeline codebase: scoping changes, providing the right files as context. Compensation and Benefits Salary Range $96,800.00 - $137,000.00 USD Pay is determined based on experience, qualifications, and location. Salaried employees may also be eligible for discretionary bonuses, profit-sharing, and long-term incentives for Executive-level roles.
Location & working pattern

Piscataway, NJ, US

For additional Colgate terms and conditions, please click here. #LI-Hybrid
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