Lead Data Engineer

3M

Confirmed live 2 days ago High trust
Remote

Quick summary

Work type
Remote
Location
MN
Salary
$188,251–$230,084 / yr
Posted
26 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $180k
This role $209k
$139k most similar roles pay here $240k

This role pays more than 64% of similar roles. Most pay $149,106–$211,200 — the shaded band above. At the midpoint, this role pays about $209k versus about $180k for comparable roles.

Based on 240 similar postings.

Employer

About 3M

3M is a diversified technology and manufacturing conglomerate producing thousands of products across healthcare, safety, electronics, transportation, and consumer goods. Industry: Diversified Manufacturing

3M currently has 61 open roles on FindRole.

Listed pay typically runs $145,676–$178,049 across 51 roles with salary data.

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View all roles at 3M

At a glance

TL;DR · Lead Data Engineer

Lead Data Engineer The Lead Data Engineer joins a technical team to design, develop, and optimize scalable data platforms that power advanced analytics and machine learning applications across the organization. This role involves leading the architecture of secure data pipelines for AI/ML workloads, managing end-to-end processes including ingestion, transformation, storage, quality, and monitoring. The successful candidate will collaborate with data scientists to build feature stores and training pipelines while mentoring junior engineers and defining technical roadmaps. Key technologies include Python, SQL, Spark, Databricks, Synapse, and Azure components like Data Factory and Cosmos DB. Additional expertise involves workflow orchestration via Airflow, streaming platforms such as Kafka or Event Hub, and experience with vector databases or LLM-oriented pipelines. The role focuses on solving complex data modeling, governance, and performance optimization challenges for intelligent platforms.

What you'll do

  • Design and develop scalable, secure data pipelines to support AI/ML workloads across the organization.
  • Manage end-to-end data engineering processes including ingestion, transformation, storage, quality, and monitoring.
  • Partner with data scientists and ML engineers to develop model features and training pipelines.
  • Establish best practices for data modeling, orchestration, versioning, and performance optimization.
  • Mentor junior engineers and contribute to technical roadmaps and solution patterns.
  • Ensure all platforms meet data governance, lineage, and compliance standards.
  • Manage both real-time and batch processing frameworks in production environments.

What we're looking for

  • Bachelor's degree or higher in computer science from an accredited institution.
  • At least seven years of data engineering experience, including leading technical initiatives.
  • Expertise in Python, SQL, and distributed data systems like Spark, Databricks, and Synapse.
  • Experience building AI/ML ready data pipelines, feature stores, and model training data flows.
  • Hands-on experience with cloud platforms, specifically Azure services like Data Factory and Cosmos DB.
  • Strong understanding of ML concepts, lifecycle, and MLOps practices.
  • Proven experience with workflow orchestration tools such as Airflow or Synapse Pipelines.

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