Data Engineer

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Job Description

Data Engineer - IT Data Analytics Team

Job Summary

The Data Engineer will design, build, and support scalable data solutions for the IT Data Analytics team. This role will develop and optimize data pipelines, data lake and data warehouse assets, ETL/ELT processes, and CI/CD-enabled deployments that support enterprise analytics and data products. The individual will partner with analytics, product, business, and technology teams to deliver reliable, secure, and reusable data products that enable reporting, insights, and decision-making across 3M.

Primary Responsibilities

• Design, develop, and maintain data pipelines, ETL/ELT workflows, and data integration solutions.
• Build and support trusted data products, including curated datasets, reusable data assets, semantic layers, and analytics-ready data models.
• Support data lake, data warehouse, and analytics platform configuration, optimization, and operations.
• Apply DevOps practices, including CI/CD, version control, automated testing, and deployment automation for data engineering solutions.
• Monitor data quality, pipeline performance, platform reliability, and production support processes.
• Partner with product owners, analysts, architects, and stakeholders to translate business needs into scalable data solutions.
• Implement security, access control, backup, recovery, documentation, and operational standards for data platforms and data products.
• Troubleshoot complex technical issues and drive continuous improvement in data engineering practices, tools, and delivery standards.

Preferred Qualifications

• Bachelor’s degree in computer science, information technology, management information systems, mathematics, engineering, or a related field.
• 5+ years of experience in data engineering, data warehouse development, or analytics platform support.
• Experience with SQL, Python, ETL/ELT development, data modeling, and data quality practices.
• Experience with data platforms and tools such as Snowflake, Azure, Power BI, or similar technologies.
• S/4HANA or SAP HANA knowledge helpful.
• AWS stack experience preferred, including services supporting data lake, storage, compute, orchestration, and analytics workloads.
• Databricks experience preferred, including notebook development, data engineering workflows, or Lakehouse architecture.
• Experience supporting data lakes, data products, analytics solutions, APIs, or integration development.
• Familiarity with DevOps, CI/CD pipelines, Git-based version control, automated testing, and deployment automation.
• Strong communication, problem-solving, and technical troubleshooting skills.
• Ability to work independently, manage multiple priorities, and deliver results in a fast-paced environment.

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