Azure Data Engineer

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 efficient 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