Wearables & IoT Data Engineer - AI-Ready Pipelines

Hill's Pet Nutrition; Topeka (KS); On-site; USD 115,000 - 130,000; Full time

Benefits offered by this job

Medical, dental, vision

15 vacation days

13 paid holidays

401(k) with company match

Job summary

Colgate-Palmolive invites applications for a Data Engineer, Wearables within the Data Science and Engineering team in Topeka, KS. You will own end-to-end data pipelines, transforming wearable sensor data into AI-ready datasets and collaborating across clinical, claims, and nutrition teams to advance analytics.

The role emphasizes data governance, scalable pipelines, and partnership with external vendors to drive data-driven product decisions.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Statistics, or related discipline.
• 4+ years in data engineering, data science, or analytics.
• Cloud experience (preferably GCP) with SQL and Python or R.
• Experience with time-series or multi-source study data.

Responsibilities

• Automated Pipeline Development & Orchestration: design, build, and maintain scalable data pipelines across cloud and enterprise platforms.
• Cross-Functional Data Integration & Analytics Support: integrate wearable data with study datasets and harmonize endpoints.
• Vendor & Infrastructure Technical Leadership: manage third-party device manufacturers and data vendors.
• Unstructured & AI-Ready Data Management: organize time-series datasets with lineage and feature stores for ML models.

Skills

SQL

Python/R

Time-series data

Data pipelines

Cloud data environments

Data analysis

Education

Bachelor's degree in CS/Engineering/Statistics

Master's or PhD preferred

Tools

BigQuery

Snowflake

SAP

Airflow

dbt

Cloud Composer

Git

Job description

Colgate-Palmolive invites applications for a Data Engineer, Wearables within the Data Science and Engineering team in Topeka, KS. You will own end-to-end data pipelines, transforming wearable sensor data into AI-ready datasets and collaborating across clinical, claims, and nutrition teams to advance analytics.

The role emphasizes data governance, scalable pipelines, and partnership with external vendors to drive data-driven product decisions.