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# Data Engineer

- **Company:** Freudenberg Sealing Technologies
- **Location:** Plymouth, MI, United States
- **Salary:** $120,000
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Microsoft Azure, Cloud Engineering, Cloud Storage, Databases, Information Engineering, Data Files, Database Testing, Apache Hive, Python (Programming Language), Operational Databases, Systems Development Life Cycle, Role-Based Access Control, Cloud Services, Standard Sql, SQL Databases, Data Streaming, Enterprise Software Applications, Data Lakes, Pyspark, Information Technology, Data Analytics, Key Vault, Databricks
- **Published:** November 8, 2026
- **Apply:** https://www.careerbuilder.com/job-details/data-engineer-plymouth-mi--816aa22f-ce0b-47bb-a606-1269010d7525

## About the Role

Business Operations, Automotive Industry, Health Insurance, Team Building, SQL (Structured Query Language), Scalable System Development, Microsoft Windows Azure, Application Programming Interface (API), Cloud Storage, Data Sets, * Degree in Computer Science, Data Engineering, or related field (or equivalent experience).

 * Proven experience building and running production data pipelines and data products.
 * Strong Python, PySpark, Spark SQL, and SQL skills.
 * Hands-on experience with Databricks (Delta Lake, Unity Catalog, Jobs/workflows, SQL Warehouses).
 * Familiarity with cloud data platforms (Azure preferred; ADLS, Blob, Key Vault, RBAC or similar).
 * Experience with data testing, validation, and quality frameworks.
 * Strong collaboration and communication skills with a practical, solution-oriented mindset.

## Description

* Build scalable lakehouse pipelines on Azure Databricks using PySpark, Spark SQL, and Delta Lake.
 * Ingest and unify data from enterprise systems, APIs, databases, cloud storage, and file-based sources.
 * Deliver trusted, analytics-ready data products including curated datasets and feature-ready tables.
 * Productionize Databricks solutions (workflows, Unity Catalog, Delta tables, SQL Warehouses) with strong reliability.
 * Implement automated data quality, validation, and secure access patterns across pipelines.
 * Optimize performance and cost while modernizing legacy data flows into cloud-native architectures.
 * Partner with business, IT, and data teams to deliver high-impact, data-driven solutions.