Lead Data Engineer

Remote

Quick summary

Work type: Remote
Location: Remote
Salary: $188,251–$230,084 / yr
Posted: 9 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $175k

This role $209k

$128k most similar roles pay here $241k

This role pays more than 71% of similar roles. Most pay $139,075–$211,200 — the shaded band above. At the midpoint, this role pays about $209k versus about $175k 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 43 open roles on FindRole.

Listed pay typically runs $145,676–$178,049 across 39 roles with salary data.

Most-posted roles

View all roles at 3M

At a glance

TL;DR · Lead Data Engineer

Role Posting Log in to save

Join our dynamic team as a Lead Data Engineer and lead the design, development, and optimization of data platforms that power advanced analytics and machine learning applications. You will architect scalable, secure data pipelines supporting AI/ML workloads, own end-to-end data engineering processes including ingestion, transformation, storage, quality, and monitoring, and collaborate with data scientists on model features and training pipelines. Mentor junior engineers, drive best practices in data modeling and orchestration, and ensure compliance standards are met across platforms. Ideal candidates have seven or more years of data engineering experience, expertise in Python, SQL, Spark, Databricks, and Azure Data Factory, hands-on experience with cloud platforms, workflow orchestration tools like Airflow, and streaming platforms such as Kafka. This role requires a strong understanding of ML concepts and MLOps practices, and the ability to translate business needs into technical solutions.

Skills

Python SQL Spark Databricks Azure Data Lake Azure Data Factory Airflow Kafka DevOps CI/CD Terraform Vector databases LLM oriented data pipelines Cosmos DB Event Hub Synapse Pipelines MLOps

What you'll do

Lead the design and development of scalable, secure data pipelines for AI/ML workloads.
Own end-to-end data engineering processes including ingestion, transformation, storage, quality, and monitoring.
Drive best practices in data modeling, orchestration, versioning, and performance optimization.
Mentor junior engineers and contribute to technical roadmaps and solution patterns.
Ensure compliance with data governance, lineage, and security standards across platforms.
Support real-time and batch processing frameworks in production environments.

What we're looking for

Bachelor's degree in computer science and at least 7 years of data engineering experience, including leadership roles.
Expertise in Python, SQL, and distributed data systems like Spark, Databricks, and Synapse.
Experience building AI/ML data pipelines, feature stores, and model training flows.
Hands-on experience with cloud platforms (preferably Azure) for data storage and processing.
Strong understanding of ML lifecycle, MLOps practices, and workflow orchestration tools.
Familiarity with streaming platforms like Kafka and vector databases for LLM-oriented data pipelines.
Background in DevOps, CI/CD, or infrastructure as code for scalable data architectures.

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