Sr Data Engineer

Milwaukee Tool

Menomonee Falls (WI)

On-site

USD 120,000 - 180,000

Full time

3 days ago

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Benefits offered by this job

Health, dental and vision insurance

Generous 401(k) savings plan

Education assistance

On-site wellness and coffee service

Job summary

Milwaukee Tool is seeking a Senior Data Engineer to design, build, and support scalable data pipelines and data models that enable fast, data-driven decisions across the organization.

You will collaborate with business partners and the Data Platform team to deliver enterprise-grade data solutions, governance, and self-service tooling while mentoring others and advancing engineering practices.

Qualifications

Bachelor’s degree in Computer Science, Information Systems or equivalent experience.
5 to 8+ years of experience in data engineering or a related technical field.
Expertise in SQL and advanced proficiency in at least one programming language (Python preferred).
Extensive hands-on experience building scalable pipelines and workflows in Databricks (Delta Lake, Spark, Unity Catalog, Jobs, Workflows).
Strong experience designing and tuning distributed data processing systems at scale.

Responsibilities

Design and build scalable data pipelines to ingest, transform, and curate data from APIs, databases, files, and event streams.
Lead technical design reviews and translate complex business needs into enterprise-grade data solutions.
Develop and optimize advanced data models to support analytics, BI, and productized datasets.
Champion SDLC best practices, CI/CD, and Infrastructure-as-Code for data infrastructure.
Optimize distributed workloads (SQL, Python, Spark) and mentor others on design patterns.
Build reusable data frameworks and reference architectures to accelerate platform adoption.
Perform root-cause analysis for major data incidents and drive remediation.
Provide technical mentorship and guide code reviews for Data Engineers.
Collaborate with Architects and Product Owners to define long-term data strategies.

Skills

SQL

Python

Databricks

Spark

CI/CD

Data modeling

Distributed systems

Mentorship

Agile

Education

Bachelor’s degree in Computer Science or equivalent

Tools

Databricks Unity Catalog

Delta Live Tables

Databricks Workflows

Purview/Collibra/Alation

Job description

Applicants must be authorized to work in the U.S.; Sponsorship is not available for this position.

INNOVATE without boundaries!

At Milwaukee Tool we firmly believe that our People and our Culture are the secrets to our success- so we give you unlimited access to everything you need to provide support to your business unit. Behind our doors you'll be empowered every day to own it, drive it, and do what it takes to support the biggest breakthroughs in the industry. Meanwhile, you'll have the support and resources of the fastest-growing brand in the construction industry to make it happen.

Your Role On Our Team

As a Senior Data Engineer, you will deliver innovative data products that enable Milwaukee Tool to make fast, data-driven decisions. Working closely with business partners and the Data Platform team, you will design, build, and support the core systems that power our data platform. You will create scalable data pipelines, self-service tools, and governance solutions that ensure trusted, accessible data across the organization. You’ll develop deep knowledge of our data and support advanced analytics, including machine learning. Success in this role requires curiosity, a passion for experimentation, and a drive to share knowledge to elevate the team and benefit our customers.

You’ll Be DISRUPTIVE Through These Duties And Responsibilities

Design and build scalable data pipelines to ingest, transform, and curate data from a variety of systems including APIs, databases, files, and event streams.
Lead technical design reviews, translate complex business needs into enterprise-grade data solutions, and influence data engineering best practices across teams.
Develop and optimize advanced data models (dimensional, data vault, domain-driven, canonical models) to support analytics, BI, and productized datasets.
Champion engineering excellence through SDLC best practices, continuous delivery, and data infrastructure automation using CI/CD and Infrastructure-as-Code.
Optimize complex distributed workloads including SQL, Python, and Spark; mentor others on advanced tuning techniques and scalable design patterns.
Build reusable data frameworks, libraries, and reference architectures to accelerate team productivity and platform adoption.
Perform root‑cause analysis for major data incidents, lead long-term remediation, and influence operational reliability improvements.
Provide technical mentorship to Data Engineers, guide code reviews, and help shape engineering capability maturity.
Collaborate with Architects, Data Leads, Product Owners, and cross‑functional engineering teams to define long‑term data strategies.
Performs other duties as assigned.

The TOOLS You’ll Bring With You

Bachelor’s degree in Computer Science, Information Systems or equivalent experience.
5 to 8+ years of experience in data engineering or a related technical field.
Expertise in SQL and advanced proficiency in at least one programming language (Python preferred).
Extensive hands‑on experience building scalable pipelines and workflows in Databricks (Delta Lake, Spark, Unity Catalog, Jobs, Workflows).
Hands‑on experience with distributed data processing technologies such as Apache Spark.
Strong experience designing and tuning distributed data processing systems at scale.
Proven experience designing and implementing complex data models across multiple business domains.
Strong knowledge of version control, CI/CD, DevOps/DataOps, automated testing, and engineering best practices.
Ability to lead cross‑functional engineering initiatives and influence technical roadmaps.
Strong problem‑solving, debugging, and analytical skills, especially in complex, multi‑system environments.
Ability to thrive in agile, dynamic, and collaborative engineering teams.

Other TOOLS We Prefer You To Have

Experience with Databricks Unity Catalog, Delta Live Tables, or Databricks Workflows.
DataOps experience (pipeline observability, monitoring, automated quality).
Knowledge of metadata management or cataloging platforms (Purview, Collibra, Alation).
Experience with streaming frameworks (Kafka, Event Hubs, Kinesis) used with Spark Structured Streaming.
Knowledge and experience working in an Agile environment.
Experience working with retail product promotion data.

Working Conditions

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Frequently required to stand, walk, bend, stretch, reach, and effectively communicate with others in the workplace
Sitting for prolonged periods of time
Prolonged exposure to computer screens
Repetitive use of hands and fingers to operate office equipment, machinery, hand tools and/or power tools
Specific vision abilities required by this job include close vision, color vision, peripheral vision, depth perception, and ability to adjust focus
May require to wear personal protective equipment which includes, but is not limited to, safety glasses, gloves, and hearing protection
May work in laboratories and/or controlled, enclosed, restricted areas
Noise levels range from moderate to loud
Must be able to lift up to 50 pounds at a time
May require travel dependent on company needs

We Provide These Great Perks And Benefits