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Working at Freudenberg: We will wow your world!
Responsibilities:
- 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.
Qualifications:
- 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.
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The Freudenberg Group is an equal opportunity employer that is committed to diversity and inclusion. Employment opportunities are available to all applicants and associates without regard to race, color, religion, creed, gender (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity or expression, national origin, ancestry, age, mental or physical disability, genetic information, marital status, familial status, sexual orientation, protected military or veteran status, or any other characteristic protected by applicable law.
Freudenberg-NOK General PartnershipLearn more about this Employer on their Career Site
