Plant Manager leading operations at ZF's Electronics Plant in Częstochowa, driving performance and efficiency while ensuring strategic alignment with company goals.
About the role
- Databricks Data Engineer responsible for building and optimizing scalable data pipelines using Databricks. Requires strong experience in data engineering and distributed data processing.
Responsibilities
- Design, build, and maintain ETL/ELT pipelines on Databricks using PySpark, Spark SQL, and Delta Lake.
- Develop and optimize data ingestion frameworks, data transformations, and end‑to‑end workflows for batch and streaming use cases.
- Implement Delta Lake‑based architectures, including versioning, schema evolution, and ACID‑compliant pipelines.
- Work with stakeholders to understand data requirements and translate them into scalable data engineering solutions.
- Manage and optimize Databricks clusters, jobs, and notebooks for performance and cost efficiency.
- Ensure data quality, reliability, and observability through validation frameworks and monitoring.
- Contribute to data modeling, metadata management, and best practices within the data platform.
- Collaborate closely with data scientists, analysts, and business teams to support analytics and ML workloads.
Requirements
- Graduate in Computer Science, Data Science, or related field.
- 5+ years of experience in data engineering with 3+ years of hands on expertise in Databricks.
- Hands-on experience with Spark (PySpark/Spark SQL) and distributed data processing.
- Solid SQL knowledge and experience working with large-scale datasets
- Strong understanding of Delta Lake, medallion architecture, and scalable lakehouse patterns.
- Good understanding of CI/CD, Git, and modern DevOps practices for data pipelines.
- Familiarity with structured/unstructured data, data quality frameworks, and performance tuning.
Benefits
- Mandatory 5 days work from office in Gurgaon.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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