Sr Specialist, Data Engineering

• 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.
• Operate the on-call and incident response cycle for owned pipelines: triage failures, perform root-cause analysis, write post-mortems, and convert recurring issues into permanent fixes.
• Implement pipelines to platform standards — branching strategy, CI/CD for dbt and Airflow, code review norms, documentation, naming conventions
• Stay current on the evolving data engineering stack (agentic tooling, streaming patterns, observability frameworks) and bring grounded recommendations on what to adopt and what to skip.

• Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related quantitative discipline.
• A Master's degree in a relevant field is an advantage but not required.
• Equivalent practical experience or demonstrable self-taught expertise will be considered in lieu of formal qualifications.

• 2 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.
• 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.
• Comfortable working with Git in a team environment, including branching strategies, pull requests, and code reviews.
• Hands-on experience using agentic coding environments (Claude Code, Cursor, Windsurf, or similar) as a working partner for planning, writing, and refactoring production code scoping multi-step changes, supplying the right context, and course-correcting across files.
• Fluency in driving an AI coding tool across pipeline codebase: scoping changes, providing the right files as context.

• Experience working with Google Cloud Platform (GCP) services such as Cloud Storage, GKE
• Familiarity with containerisation using Docker, including writing Dockerfiles and managing containerised workloads.
• Exposure to container orchestration with Kubernetes for deploying and scaling data services.
• Knowledge of streaming or event-driven data architectures using tools like Pub/Sub, or Kinesis.
• Experience with data observability and quality frameworks such as DQ Labs, Elementary, or Great Expectations.
• Familiarity with CI/CD pipelines and DevOps practices applied to data workflows (GitHub Actions, Cloud Build, or similar).
• Familiarity with the emerging pattern of agentic data engineering — using LLM-driven agents or workflows to automate routine pipeline tasks and a point of view on what should and should not be delegated to an agent.
• Sound judgment on when AI-generated output needs to be challenged, rewritten, or discarded particularly around security, data privacy, PII handling, edge cases, performance, and idempotency.

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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, colour, 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. #LI-Hybrid