AWS Databricks Lead

Required Skills 9-13 years of experience in Data Engineering. Strong hands-on experience with Databricks, PySpark, and Apache Spark. Expertise in designing and developing ETL/ELT pipelines and data transformation workflows. Experience with AWS services such as S3, Glue, IAM, Lambda, EMR, and Redshift. Strong SQL skills and experience with relational databases. Good understanding of Data Lake/Lakehouse architecture and Delta Lake. Experience with workflow orchestration tools such as Airflow. Knowledge of Git, CI/CD practices, and production support. Strong performance tuning, troubleshooting, and optimization skills. Nice to Have Kafka, Spark Streaming Snowflake, Apache Iceberg, dbt Terraform AWS or Databricks Certifications Responsibilities Build and maintain scalable data pipelines on Databricks and AWS. Develop batch and real-time data processing solutions. Collaborate with business and technical teams to deliver data solutions. Ensure data quality, governance, security, and operational excellence. Optimize Spark workloads and support production environments.