Sr Data Engineer

Milwaukee Tool is a construction industry brand that emphasizes innovation, people, and culture. The Senior Data Engineer will design, build, and support scalable data platforms, pipelines, models, self-service tools, and governance solutions that enable data-driven decisions and advanced analytics, including machine learning.

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

Requirements:

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