What you can look forward to as Azure Data Engineer

- End-to-End Ownership: Lead and drive analytics initiatives, ensuring high-quality deliverables with minimal oversight
- Structured Software Development: Apply engineering best practices, including CI/CD, version control, testing, and code reviews, to ensure robust, maintainable, and scalable solutions
- Design, implement, and scale reliable and productive data models and pipelines in Databricks, Azure Cloud, and other relevant platforms to support analytics and AI initiatives
- Lead AI & ML initiatives, according to AI & automation roadmap of analytics team
- Data Modeling & Optimization: Develop efficient data models, ensuring high performance for analytical workloads and business intelligence applications
- Ensure seamless integration of data products with BI tools, APIs, and other business applications, providing structured, well-documented, and high-quality datasets

Your profile as Azure Data Engineer





- Degree in computer science, math or engineering with emphasis on machine learning / analytics or equivalent in experience
- 5-11 years of experience in Azure Data engineering, Analytics or AI/ML integration
- Strong experience in Python, R and Spark (Pyspark is desirable)
- Deployment of ML models in production & Industry experience in agile development and DevOps Databases (ex. Oracle, AWS S3)
- Big Data Platforms (ex. Databricks, GCP, Cloudera) & Soft skills include working well in teams dealing with uncertainty and ambiguity, flexibility
- Deep understanding of structured software development practices (version control, CI/CD, testing) & Excellent problem-solving skills and ability to work independently on complex projects

Skills: Devops, Pyspark, Azure, Python

Experience: 5.00-11.00 Years

📌 Azure Data Engineer (Pune)
🏢 Zf Lifetec India
📍 Pune