Data Driven Innovation Specialist

1 day ago

Pune, Maharashtra, India beBeeData Full time ₹ 1,50,40,000 - ₹ 2,25,60,000
Advanced Analytics Position

We are seeking a highly skilled Product Data Analyst to join our team at ZF Friedrich. As a key member of our Data Engineering department, you will be responsible for driving and managing analytics initiatives from concept to deployment.

About the Team:

ZF Aftermarket is a global leader in the automotive and industrial markets, with a presence in 40 countries worldwide. Our team of over 8,000 employees works together to provide innovative solutions that meet the needs of our customers.

Your Responsibilities:

  • Drive and manage analytics initiatives from concept to deployment, ensuring high-quality, timely deliverables with minimal supervision.
  • Apply structured software development principles, including version control, CI/CD, automated testing, and peer code reviews to ensure robust, scalable, and maintainable solutions.
  • Design, build, and optimize scalable and reliable data models and pipelines in Databricks, Azure Cloud, and other big data environments to support advanced analytics and AI use cases.
  • Develop and maintain high-performance data models tailored for analytical workloads and business intelligence use.
  • Serve as a key liaison between technical teams and business stakeholders to understand needs, validate outcomes, and ensure solutions are actionable and business-ready.
  • Create insightful and user-centric dashboards using tools like Power BI, Shiny for Python/R, or similar platforms.

Requirements:

  • 8-10 years of experience in Data Engineering/ Advanced analytics roles.
  • Hands-on experience with Databricks, Azure, and familiarity with Big Data platforms (e.g., GCP, Cloudera).
  • Prior experience with Data Bricks, Python, Pysprak, TecDoc or product data in the automotive domain.
  • Industry experience in agile development and DevOps Databases (ex. Oracle, AWS S3).
  • Proficiency with data visualization tools such as Power BI, Shiny, or equivalent.

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