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Lead Data Integration Engineer - Kimberly Clark
Implementation Engineer
Lead Data Integration Engineer responsible for designing and building scalable ETL/ELT pipelines, data models, and ingestion frameworks using Python, Spark, Azure Data Factory, Snowflake, and SAP HANA.
About the role
Key Responsibilities
- Collaborate with technical architects, product owners, and business stakeholders to translate business requirements into robust data integration designs.
- Design, develop, and maintain reusable ETL/ELT pipelines and frameworks leveraging Python, Spark, Azure Data Factory, Snowpipe, and Snowflake.
- Build and optimize complex SQL queries for data processing in SAP HANA, Azure, and Snowflake environments.
- Create and maintain logical and physical data models to support enterprise data warehousing initiatives.
- Establish best practices for data ingestion, transformation, and quality assurance across the data platform.
Requirements
- 5+ years of experience in data warehousing, data modeling, and ETL/ELT development.
- Strong proficiency in Python, Spark, SQL, and cloud data services (Azure Data Factory, Snowflake, SAP HANA).
- Hands‑on experience designing scalable data pipelines and reusable integration frameworks.
- Ability to work cross‑functionally with architects, product owners, and business teams to deliver data solutions.
- Excellent problem‑solving skills and a track record of optimizing data processing performance.
Skills
pythonsnowflakesap hanasql