Sr Manager IT- Data Engineering

Milwaukee-Tool; Menomonee Falls (WI); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Health benefits

401(k) savings plan

Education assistance

On-site wellness & fitness

Job summary

Milwaukee Tool is seeking a Senior Manager of Data Engineering to lead teams responsible for enterprise data products and the Databricks-based lakehouse platform. You will drive reliable delivery, engineering quality, and strong partnerships across analytics, governance, security, and technology teams.

The role emphasizes AI-native engineering, scalable data pipelines, and modernization while ensuring security, data governance, and production controls.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field or equivalent experience.
• 7+ years of progressive data engineering and software engineering experience, including at least 3 years leading teams.
• Experience delivering enterprise-scale data platforms and data pipelines in cross-functional environments.
• Hands-on depth with Databricks, Spark, Delta Lake, and Unity Catalog.
• Strong Python and SQL skills, CI/CD, IaC, and cloud-native delivery.

Responsibilities

• Lead and develop data engineering managers, tech leads, and engineers; set accountability and career paths.
• Build an inclusive, high-performing culture grounded in ownership and collaboration.
• Translate strategy into priorities, roadmaps, and measurable outcomes; manage budgets and vendor relations.
• Own delivery and operation of scalable data pipelines and platform capabilities for analytics, AI, and ML use cases.
• Lead Databricks platform initiatives, migration of legacy pipelines, and cost management.
• Define and scale AI-native engineering practices with governance and security in mind.

Skills

Leadership

Team management

Strategic planning

Communication

Stakeholder management

Problem solving

Education

Bachelor's degree in CS/IS/Engineering

7+ years data engineering/leadership experience

Tools

Databricks

Apache Spark

Delta Lake

Unity Catalog

Databricks Workflows

Azure Data Lake Storage

Job description

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 technical solutions on our IT Team.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:The Senior Manager of Data Engineering leads teams that design, build, operate, and continuously improve enterprise data products and platforms. Reporting to the Director of Data Engineering, this leader is accountable for reliable delivery, engineering quality, team development, and strong partnerships across business, analytics, architecture, governance, security, and technology teams.This role will advance our Databricks-based data platform and establish practical AI-native engineering capabilities. The Senior Manager will use AI-assisted and agentic development approaches to improve how teams design, code, test, document, deploy, monitor, and support data solutions while maintaining appropriate human oversight, security, data governance, and software engineering controls.You'll be DISRUPTIVE through these duties and responsibilities:Leadership and Team Management· Lead, coach, and develop data engineering managers, technical leads, and engineers; establish clear accountability, performance expectations, career paths, and succession plans.· Build an inclusive, high-performing engineering culture grounded in ownership, technical excellence, collaboration, and continuous learning.· Translate enterprise strategy into priorities, capacity plans, delivery roadmaps, and measurable outcomes.· Manage employee and partner capacity, budgets, and vendor relationships to deliver the highest-value work efficiently.· Communicate effectively with executives, business leaders, architects, product leaders, and technical teams.Data Engineering Strategy and Delivery· Own the delivery and operation of scalable data pipelines, reusable frameworks, curated data products, and platform capabilities supporting analytics, reporting, operational, AI, and machine learning use cases.· Partner with product and business leaders to define outcomes, prioritize demand, manage dependencies, and deliver incremental business value.· Establish engineering standards for architecture, coding, testing, CI/CD, observability, documentation, performance, reliability, and supportability.· Improve delivery predictability through portfolio management, agile planning, transparent metrics, risk management, and disciplined execution.· Reduce technical debt and operational burden through modernization, automation, reusable patterns, and intentional lifecycle management.· Lead incident response and problem management for critical data services, including root-cause analysis and corrective action.Databricks Platform Leadership· Provide technical and operational leadership for the Databricks Lakehouse platform, including Delta Lake, Unity Catalog, workflows, compute, security, observability, and cost management.· Guide migration and modernization of legacy data pipelines and warehouse workloads to scalable Databricks patterns where they provide clear value.· Establish reusable ingestion, transformation, orchestration, data quality, deployment, and monitoring frameworks.· Optimize platform performance and cost through workload design, cluster and serverless strategies, usage transparency, and FinOps practices.AI Native Engineering and AI Enablement· Define and scale responsible AI-assisted development practices across requirements, design, code generation, review, testing, documentation, deployment, and operations.· Evaluate agentic engineering capabilities that automate bounded workflows while preserving human approval, traceability, security, and production controls.· Set measurable adoption and effectiveness goals for AI development tools, including cycle time, quality, test coverage, developer experience, and incident reduction.· Ensure AI-generated code and artifacts meet enterprise standards for security, privacy, maintainability, intellectual property, testing, and peer review.· Partner with AI and data science teams to provide trusted data products, feature pipelines, vector and unstructured data patterns, and model or agent telemetry.Data Governance Reliability and Security· Embed data ownership, metadata, lineage, classification, access controls, retention, and quality rules into engineering workflows and platform services.· Define service-level objectives and metrics for data freshness, quality, availability, performance, cost, and recovery.· Partner with cybersecurity, privacy, risk, and compliance teams to ensure data products and AI-enabled workflows meet enterprise requirements.Performs other duties as assigned.The TOOLS you'll bring with you:· Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent relevant experience.· 7 or more years of progressive experience in data engineering, software engineering, data platforms, or related disciplines, including at least three years leading engineering teams and people managers.· Demonstrated experience leading enterprise-scale data engineering delivery in a complex, cross-functional environment.· Hands-on technical depth with Databricks and Apache Spark, including Delta Lake and production pipeline design; Unity Catalog and Databricks Workflows experience is strongly desired.· Strong experience with Python, SQL, automated testing, source control, CI/CD, infrastructure as code, and cloud-native delivery.· Experience designing and operating batch and streaming pipelines, lakehouse or warehouse solutions, APIs, and event-driven integrations.· Experience implementing or governing AI-assisted development tools and practices in an enterprise engineering environment.· Working knowledge of data and AI governance, security, privacy, metadata, lineage, data quality, and production controls.· Strong business acumen, written and verbal communication, problem solving, prioritization, and executive stakeholder management skills.Other TOOLS we prefer you to have:· Experience with Microsoft Azure, including Azure Data Lake Storage, Azure DevOps, Entra ID, Event Hubs, or related services.· Experience modernizing enterprise data warehouses and ETL estates, including migration, coexistence, and decommissioning.· Experience in manufacturing, supply chain, retail, product, or other data-intensive domains.· Experience managing global teams, strategic partners, and managed services.We provide these great perks and benefits:· Robust health, dental and vision insurance plans· Generous 401 (K) savings plan· Education assistance· On-site wellness, fitness center, food, and coffee service· And many more, check out our benefits site HERE.Milwaukee Electric Tool Corporation (\"Milwaukee Tool\") is an equal opportunity and affirmative action employer seeking to employ and advance in employment qualified persons without discrimination and to not allow harassment of any employee or applicant because of race, ethnicity, color, religion, sex, sexual orientation, gender identity, genetic characteristics, physical or mental disability, national origin, age, status as a protected veteran, and any other status protected by local, state, or federal law.Milwaukee Tool is an equal opportunity employer.