Data Engineer
Lead Data Engineer responsible for designing and maintaining AI/ML data pipelines, leveraging Python, Spark, and SQL on cloud platforms to deliver scalable, high‑performance data solutions for 3M’s global operations.
Job Description:
Collaborate with Innovative 3Mers Around the World
Choosing where to start and grow your career has a major impact on your professional and personal life, so it’s equally important you know that the company that you choose to work at, and its leaders, will support and guide you. With a wide variety of people, global locations, technologies and products, 3M is a place where you can collaborate with other curious, creative 3Mers.
This position provides an opportunity to transition from other private, public, government or military experience to a 3M career.
The Impact You’ll Make in this Role: We are seeking a Lead Data Engineer with strong experience in AI/ML data pipelines, feature engineering, and scalable data architectures. This role will lead the design, development, and optimization of data platforms that power advanced analytics and machine learning applications across the organization.
Key Responsibilities
Lead the architecture and development of scalable, secure data pipelines supporting AI/ML workloads.
Own end to end data engineering processes: ingestion, transformation, storage, quality, and monitoring.
Collaborate with data scientists and ML engineers on model features, training pipelines, and deployment.
Drive best practices in data modeling, orchestration, versioning, and performance optimization.
Mentor and guide junior engineers; contribute to technical roadmaps and solution patterns.
Ensure data governance, lineage, and compliance standards are met across platforms.
Support real time and batch processing frameworks in production environments.
Your Skills and Expertise To set you up for success in this role from day one, 3M is looking for candidates who must have the following qualifications:
Bachelor's degree or higher in computer science (completed and verified prior to start) from an accredited institution.
Seven (7) or more years of data engineering experience, including leading technical initiatives.
Additional qualifications that could help you succeed even further in this role include:
Strong expertise in Python, SQL, and distributed data systems (e.g., Spark, Databricks, Synapse).
Experience building AI/ML ready data pipelines, including feature stores and model training data flows.
Hands on experience with cloud platforms (Azure preferred — Data Lake, Data Factory, Databricks, Cosmos DB).
Strong understanding of ML concepts, lifecycle, and MLOps practices.
Proven experience with workflow orchestration (Airflow, Data Factory, Synapse Pipelines, etc.).
Strong communication and ability to translate business needs into technical solutions.
Experience with streaming platforms (Kafka, Event Hub).
Familiarity with vector databases, embeddings, or LLM oriented data pipelines.
Background in DevOps, CI/CD, or infra
Posted June 22, 2026