Middle Data Engineer

We are looking for a talented and driven Data Engineer to join our customer’s team. It’s a global leader in industry, worker safety, and consumer goods. Headquartered in Maplewood, Minnesota, this multinational powerhouse produces over 60,000 innovative products, ranging from adhesives, abrasives, and laminates to personal protective equipment, window films, car-care products, and cutting-edge electronic and optical materials.

In this role, you will play a key part in building and maintaining robust data pipelines, transforming raw information into valuable insights that power analytics and business intelligence across the organization. This is your chance to work on impactful projects, sharpen your technical skills, and contribute to a company that’s shaping the future of industry and innovation.

If you are passionate about data, love solving complex problems, and want to be part of a team where your work truly makes a difference, this is the opportunity for you!

Requirements

• 3+ years of professional experience in data engineering or a related role.
• Solid proficiency with Python for data processing and automation, with at least 2-3 years of hands-on experience.
• Strong SQL skills for querying and manipulating complex datasets.
• Experience with cloud data services, preferably Azure (Azure Data Factory, Azure Databricks, Azure SQL Database, Azure Data Lake Storage).
• Hands-on experience with big data processing frameworks like Spark (PySpark) and platforms such as Databricks.
• Good understanding of data warehousing concepts, ETL processes, and data integration techniques.
• Experience in applying data quality assessment and improvement techniques.
• Experience working with various data formats, including structured, semi-structured, and unstructured data (e.g., CSV, JSON, Parquet).
• Familiarity with Agile and Scrum methodologies and project management tools (e.g., Azure DevOps, Jira).
• Good communication skills and the ability to work effectively as part of a team.

Preferred Qualifications & Skills

• Knowledge of DevOps methodologies and CI/CD practices for data pipelines.
• Familiarity with modern data platforms like Microsoft Fabric for data modeling and integration.
• Experience with consuming data from REST APIs.
• Experience with database design concepts and performance tuning.
• Knowledge of dimensional data modeling concepts (Star Schema, Snowflake Schema).
• Awareness of modern data architecture concepts such as Data Mesh.
• Experience in supporting production data pipelines.

Job responsibilities

• Develop & Maintain Data Pipelines: Develop, test, and maintain robust and efficient data pipelines using Python, SQL, and Spark on the Azure cloud platform.
• Implement Data Solutions: Implement and support end-to-end data solutions, from data ingestion and processing to storage in our data lake (Azure Data Lake Storage, Delta Lake) and data warehouse.
• Utilize Cloud Data Services: Work with Azure services like Azure Data Factory, Databricks, and Azure SQL Database to build and manage data workflows.
• Ensure Data Quality: Implement data quality checks, including data profiling, cleansing, and validation routines, to help ensure the accuracy and reliability of our data.
• Performance Tuning: Assist in monitoring and optimizing data pipelines for performance and scalability under the guidance of senior engineers.
• Code Reviews & Best Practices: Actively participate in code reviews and adhere to team best practices in data engineering and coding standards.
• Stakeholder Collaboration: Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and assist in delivering effective solutions.
• Troubleshooting: Provide support for production data pipelines by investigating and resolving data-related issues.