Data Engineer

Work Location: Hyderabad/ Bangalore/ Chennai/ Pune/ Mumbai/ Gurgaon

We are seeking an experienced Senior Data Engineer with strong hands-on expertise in Databricks and AWS to design, develop, and optimize scalable data pipelines and modern data platforms. The ideal candidate will have deep experience with big data ecosystems, cloud-based data solutions (AWS), and ETL/ELT frameworks using Python, PySpark, and SQL.
Key Responsibilities:Design, build, and maintain data pipelines and ETL workflows using Databricks (PySpark, Spark SQL) and AWS services (S3, EMR, Glue, Lambda, RDS, DynamoDB).Implement data lakehouse architectures integrating Delta Lake, Snowflake, and AWS storage layers.Develop and deploy automated and scalable data ingestion frameworks to process structured and unstructured data.Build and optimize data models (Star/Snowflake schemas) for analytical and reporting use cases.Orchestrate workflows using Airflow or similar scheduling tools; manage job dependencies and monitoring.Collaborate with analytics, data science, and business teams to deliver high-quality, reliable, and well-documented data assets.Ensure data quality, governance, and security best practices are maintained throughout pipelines.Troubleshoot and tune performance for Spark clusters and SQL queries to optimize cost and efficiency.Integrate with modern tools such as DBT, Kubernetes, and CI/CD pipelines for continuous delivery of data solutions.Required Skills & Experience:10+ years of experience in data engineering, with proven work on large-scale distributed data systems.Strong hands-on experience with Databricks (PySpark, Spark SQL, Delta Lake).Expertise in AWS Cloud Services: EMR, S3, Glue, Lambda, RDS, EC2, CloudWatch, IAM, etc.Proficiency in Python and SQL for data transformation and automation.Experience with Snowflake (SnowSQL, Snowpipe, schema design, and optimization).Solid understanding of data warehousing concepts (ETL/ELT, dimensional modeling, data partitioning).Experience with Airflow for scheduling and monitoring data pipelines.Familiarity with CI/CD tools (Jenkins, Git, Docker, Kubernetes) for automated deployments.Working knowledge of NoSQL databases (MongoDB, DynamoDB, Cassandra).Excellent debugging, problem-solving, and performance-tuning skills.