Senior Data Engineer

Are you a seasoned data professional ready to lead and innovate? NAZZTEC is seeking a highly skilled and experienced Senior Data Engineer to join our dynamic team in Bangalore. This hybrid role offers a unique opportunity to design, build, and optimize scalable, enterprise-grade data platforms using cutting-edge cloud and Lakehouse technologies. If you possess a passion for driving next-generation data engineering initiatives and thrive in a high-performance environment, we invite you to contribute your expertise to our mission as a Senior Data Engineer.

Key Responsibilities

• Lead the design, development, and deployment of robust, production-grade data pipelines, including both batch and streaming solutions.
• Architect and implement scalable data lakes and Lakehouse platforms utilizing technologies like Databricks, Delta Lake, and Medallion Architecture.
• Optimize data processing workflows using Apache Spark and PySpark, focusing on performance tuning, partitioning, and large-scale distributed computing.
• Develop and maintain complex SQL queries, stored procedures, and data validation processes for various data models (Star, Snowflake, Lakehouse).
• Drive data governance and security initiatives, including IAM, access control, Unity Catalog, data lineage, and encryption.
• Implement CI/CD practices for data engineering workflows, ensuring automated deployments and robust version control using Git.
• Provide technical leadership, conduct code reviews, mentor junior engineers, and champion best practices in data engineering.
• Contribute to large-scale data migration projects, transitioning legacy systems to modern cloud data platforms.
• Explore and apply emerging technologies in GenAI, LLMs, embeddings, and vector databases to enhance data solutions.

Requirements

• Minimum of 10 years of hands-on experience in Data Engineering, with a proven track record of technical leadership.
• Expertise in the Databricks Lakehouse Platform, including Delta Lake, Databricks Workflows, Delta Live Tables (DLT), Unity Catalog, and Medallion Architecture.
• Profound knowledge of Apache Spark and PySpark, encompassing architecture, performance tuning, and large-scale distributed processing.
• Strong proficiency in Python for developing production-grade data pipelines, automation, and modular coding with robust exception handling.
• Advanced SQL skills, including complex joins, window functions, CTEs, and query optimization.
• Extensive experience with ETL/ELT pipeline development, data modeling (Dimensional, Star, Snowflake), and Data Lake/Lakehouse architectures.
• Hands-on experience with major cloud platforms such as AWS, Azure, or GCP.
• Demonstrated ability in workflow orchestration tools like Apache Airflow.
• Solid understanding of performance optimization techniques, data skew handling, and cost optimization in distributed computing environments.
• Familiarity with GenAI, LLM fundamentals, embeddings, vector databases, and RAG concepts is a significant plus.

What We Offer

• An opportunity to work on cutting-edge data engineering projects with modern cloud and Lakehouse technologies.
• Be part of a high-performing team driving innovation in the data space.
• A competitive salary package ranging from ₹35–38 LPA.
• A stimulating hybrid work environment in Bangalore, fostering collaboration and flexibility.
• Professional growth and leadership opportunities in a forward-thinking company.