Milwaukee Tool is seeking a Senior Data Engineer to deliver innovative data products and enable fast, data-driven decisions across the business. This role focuses on building scalable, reliable data pipelines and platforms to support advanced analytics and machine learning initiatives using SQL, Python, Databricks, and Apache Spark.
The Senior Data Engineer will lead technical designs, drive engineering best practices across the SDLC, and collaborate with architects and data leaders to shape long-term data strategy while mentoring other engineers.
Responsibilities- Design and build scalable data pipelines to ingest, transform, and curate data from APIs, databases, files, and event streams.
- Develop and optimize advanced data models (dimensional, data vault, domain-driven) to support analytics and ML use cases.
- Optimize complex distributed workloads using SQL, Python, and Apache Spark on Databricks.
- Lead technical design reviews and translate complex business needs into enterprise-grade data solutions.
- Champion SDLC best practices, continuous delivery, CI/CD, and data infrastructure automation.
- Provide technical mentorship to Data Engineers and contribute to engineering capability maturity.
- Collaborate with Architects, Data Leads, and stakeholders to define and execute long-term data strategy.
- Troubleshoot and resolve production data pipeline and performance issues.
- 5–7+ years of professional experience in data engineering or related roles.
- Expert proficiency in SQL and Python.
- Extensive hands-on experience with Databricks and Apache Spark.
- Proven experience designing and building scalable data pipelines for varied sources (APIs, databases, files, event streams).
- Experience developing and optimizing dimensional, data vault, or domain-driven data models.
- Demonstrated technical leadership in design reviews and delivering enterprise-grade data solutions.
- Practical experience applying SDLC best practices, CI/CD, and automation for data infrastructure.
- Experience collaborating on data strategy and mentoring engineering teams.
- Experience with cloud platforms such as Azure or AWS.*
Skills Required
- 5-7+ years of professional experience in data engineering or related roles
- Expert proficiency in SQL and Python
- Extensive hands-on experience with Databricks and Apache Spark
- Proven experience designing and building scalable data pipelines for varied sources
- Experience developing and optimizing dimensional, data vault, or domain-driven data models
- Demonstrated technical leadership in design reviews and delivering enterprise-grade data solutions
- Practical experience applying SDLC best practices, CI/CD, and automation for data infrastructure
- Experience collaborating on data strategy and mentoring engineering teams
- Experience with cloud platforms such as Azure or AWS
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