Data Engineer II-Promo Analytics

Data Engineer II-Promo Analytics

Milwaukee Tool

Job Description

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

Your Role On Our Team

As a Data Engineer II, you will play a critical role in enabling fast, accurate, and scalable data‑driven decisions at Milwaukee Tool. You will help build and evolve the pipelines, models, and governance frameworks that power analytics for retail promotions and enterprise-wide initiatives. Partnering with business teams and Data Platform engineers, you will turn requirements into high‑quality data products using Databricks and modern cloud technologies.

Your work ensures that teams have timely, reliable, and well‑structured data to support operational reporting, strategic insights, and advanced analytics.

• Design and build scalable data pipelines to ingest, transform, and curate data from a variety of systems including APIs, databases, files, and event streams.
• Review functional requirements & design specs with Senior Data Engineers and business partners and converting to data transformations.
• Implement and maintain data models such as dimensional models, star schemas, normalized models, and data vault approaches to support analytics and BI.
• Work with Data Architects and Data Leads to optimize cloud‑based data platforms, ensuring performance, reliability, and cost‑efficient execution of data workloads.
• Develop and enforce data quality checks, lineage, and monitoring to ensure accuracy, completeness, and trust in enterprise datasets.
• Leverage your expertise within the software development lifecycle, continuous improvement, and best practices to help drive the team towards rapid success.
• Automate and operationalize data pipelines using CI/CD, Infrastructure‑as‑Code, and modern orchestration tools.
• Profile, tune, and optimize SQL, Python, and Spark workloads running in Databricks.
• Author technical documentation, promote reusable components, and contribute to engineering standards and best practices.
• Troubleshoot pipeline issues, participate in root‑cause analysis, and help maintain healthy, reliable data operations.
• Performs other duties as assigned.

• Bachelor’s degree in Computer Science, Information Systems or equivalent experience.
• 3–5 years of experience in data engineering or a related technical field.
• Strong proficiency in SQL and a programming language such as Python (preferred).
• Experience building and orchestrating data workflows in Databricks, including Delta Lake, notebooks, jobs, and workflows.
• Hands‑on experience with distributed data processing technologies such as Apache Spark.
• Experience with cloud data ecosystems (Azure, AWS, or GCP), especially Azure Databricks.
• Familiarity with cloud data warehouses such as Snowflake, Synapse, Redshift, or Big Query.
• Experience working with structured and semi‑structured data (Parquet, Avro, JSON, Delta).
• Strong understanding of version control (Git) and modern CI/CD workflows.
• Strong problem‑solving, debugging, and analytical skills.
• Ability to work effectively in agile, cross‑functional engineering teams.

• Experience with Databricks Unity Catalog, Delta Live Tables, or Databricks Workflows.
• Data Ops experience (pipeline observability, monitoring, automated quality).
• Knowledge of metadata management or cataloging platforms (Purview, Collibra, Alation).
• Experience with ML pipelines and feature engineering in Databricks.
• Familiarity 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.

• 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

• 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 Tool is an equal opportunity employer.