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Req ID 90655|GEC Chennai, India,ZF Commercial Vehicle Control Systems India Limited
About the team
We are a motivated team in central R&D at CVS helping to change the game through product digitalization and vehicle intelligence. Our focus is on building solutions for truck, bus and trailer OEMs considering bothonboard and offboard needs and requirements.
What you can look forward to as Data Engineer:
Your Profile as Data Engineer:
Why should you choose ZF Group in India
Innovative Environment:ZF is at the forefront of technological advancements, offering a dynamic and innovative work environment that encourages creativity and growth.
Career Development:ZF is committed to the professional growth of its employees, offering extensive training programs, career development opportunities, and a clear path for advancement.
Global Presence:As a part of a global leader in driveline and chassis technology, ZF provides opportunities to work on international projects and collaborate with teams worldwide.
Sustainability Focus:ZF is dedicated to sustainability and environmental responsibility, actively working towards creating eco-friendly solutions and reducing its carbon footprint.
Employee Well-being:ZF prioritizes the well-being of its employees, providing comprehensive health and wellness programs, flexible work arrangements, and a supportive work-life balance.
Be part of our ZF team as Data Engineer and apply now!
Contact
Abdul Rahim J
Job ID: 152570305
Skills:
Adf, Pyspark, Scala, SQL Server, Kafka, Azure Sql, Sql, Azure Data Lake, Databricks, Informatica Powercenter, Cosmos DB, Oracle, Informatica IDMC, big data processing
Skills:
Azure, Databricks, Azure Sql, Python, Sql, Spark
Skills:
Azure Sql, Azure Data Lake, Azure Databricks, Azure Data Factory
Skills:
Python, Pyspark, Sql, Azure Devops
Skills:
Pyspark, Apache Spark, Sql, Apache Airflow, Azure Synapse, Azure Data Factory, Cosmos DB, Python, Databricks on Azure, ADLS Gen2, Azure Key Vault, Delta Live Tables, Databricks Unity Catalog, Cloud databases, Delta Lake, Lakehouse architecture, Autoloader, Databricks Workflows