Data Engineer - Remote

About The Company

3M is a global leader in innovation, dedicated to applying science to improve lives worldwide. With a diverse portfolio of products spanning industries such as healthcare, consumer goods, transportation, and manufacturing, 3M fosters a culture of creativity, collaboration, and continuous improvement. The company values its employees and provides a dynamic environment where curiosity and ingenuity are encouraged. As a company committed to sustainability and social responsibility, 3M strives to develop solutions that address some of the world's most pressing challenges, making a positive impact on communities and the environment.

About The Role

The Lead Data Engineer role at 3M offers an exciting opportunity for experienced professionals to lead the development of advanced data platforms supporting AI and machine learning initiatives. This position involves designing, building, and optimizing scalable and secure data pipelines that enable sophisticated analytics and AI applications across the organization. The successful candidate will collaborate closely with data scientists, ML engineers, and business stakeholders to translate complex requirements into robust technical solutions. This role is pivotal in ensuring the seamless flow of data, high-quality feature engineering, and deployment of models in production environments. Located remotely within the US, this full-time position supports 3M’s commitment to innovation and data-driven decision-making, offering a chance to make a significant impact within a global enterprise.

Qualifications

• Bachelor’s degree or higher in computer science, data science, or a related field from an accredited institution.
• Seven (7) or more years of proven experience in data engineering, including leading complex technical initiatives.
• Expertise in Python, SQL, and distributed data processing frameworks such as Spark, Databricks, or Synapse.
• Hands-on experience in building AI/ML-ready data pipelines, feature stores, and training data workflows.
• Proficiency with cloud platforms, preferably Azure, including Data Lake, Data Factory, Databricks, and Cosmos DB.
• Strong understanding of machine learning concepts, lifecycle, and MLOps practices.
• Experience with workflow orchestration tools like Airflow, Data Factory, or Synapse Pipelines.
• Knowledge of streaming platforms such as Kafka or Event Hub.
• Familiarity with vector databases, embeddings, and LLM-oriented data pipelines.
• Background in DevOps, CI/CD, or infrastructure as code.
• Excellent communication skills with the ability to translate business needs into technical solutions.
• Legal authorization to work in the US without sponsorship.

Responsibilities

• Lead the architecture and development of scalable, secure data pipelines supporting AI/ML workloads.
• Manage end-to-end data engineering processes, including data ingestion, transformation, storage, quality assurance, and monitoring.
• Collaborate with data scientists and ML engineers to define model features, training pipelines, and deployment strategies.
• Implement best practices in data modeling, orchestration, version control, and performance tuning.
• Mentor junior data engineers, providing guidance and technical leadership.
• Contribute to the development of technical roadmaps and solution patterns aligned with organizational goals.
• Ensure compliance with data governance, lineage, and security standards across platforms.
• Support real-time and batch data processing frameworks in production environments, ensuring reliability and scalability.

Benefits

• Competitive salary range of $188,251 - $230,084, including base pay and variable incentives.
• Comprehensive health benefits including Medical, Dental, and Vision coverage.
• Health Savings Accounts (HSAs) and Flexible Spending Accounts (FSAs) for healthcare and dependent care.
• Disability benefits, life insurance, and voluntary benefits to support your well-being.
• Paid time off, holidays, and retirement benefits to secure your financial future.
• Opportunities for professional development, training, and career advancement.
• A collaborative and innovative work environment that values diversity and inclusion.