Sr Data Engineer

tti; Menomonee Falls (WI); On-site; USD 120,000 - 160,000; Full time

Job summary

Milwaukee Tool is seeking a Senior Data Engineer to deliver scalable data products that empower fast, data‑driven decisions. You will design, build, and support core systems powering our data platform, creating scalable pipelines and governance solutions for trusted data across the organization.

You will collaborate with business partners and the Data Platform team to enable advanced analytics and ML, mentor teammates, and drive best practices across engineering teams, while supporting our

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).
• 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.

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 business needs into enterprise‑grade data solutions.
• Develop and optimize data models to support analytics, BI, and productized datasets.
• Champion SDLC best practices, continuous delivery, and infrastructure automation.
• Optimize distributed workloads using SQL, Python, and Spark; mentor others on tuning techniques.
• Build reusable data frameworks and reference architectures to speed platform adoption.
• Perform root‑cause analysis for major data incidents and drive remediation.
• Provide technical mentorship to Data Engineers and shape engineering capabilities.
• Collaborate with Architects and cross‑functional teams to define long‑term data strategies.
• Perform other duties as assigned.

Skills

Analytical thinking

Problem solving

Collaboration

Education

Bachelor's degree in Computer Science or equivalent

Tools

Databricks (Delta Lake, Unity Catalog, Jobs, Workflows)

Apache Spark

Kafka / Event Hubs / Kinesis

Purview / Collibra / Alation

Git / CI/CD / DevOps

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 p