AWS Databricks Engineer

Job highlights

• 5+ years experience with Databricks, Spark, PySpark, SQL, and AWS services (S3, Glue, Redshift, Lambda)
• Design and develop scalable data pipelines, build ETL/ELT workflows, optimize Databricks performance, implement data governance, and collaborate with stakeholders

Role: AWS Data Bricks

Experience: 5+ Years

Location: Gurgaon

Job Description:
We are looking for a skilled AWS Databricks Engineer to design, build, and optimize scalable data pipelines and analytics solutions on cloud platforms. The ideal candidate should have strong hands-on experience with Databricks, Spark, and AWS services.

Key Responsibilities:

• Design and develop scalable data pipelines using Databricks and Apache Spark
• Build ETL/ELT workflows using Python, SQL, and PySpark
• Integrate data from multiple sources (structured & unstructured)
• Optimize data processing and performance on Databricks clusters
• Work with AWS services like S3, Glue, Redshift, Lambda, EC2, and RDS
• Implement data governance, security, and best practices
• Collaborate with data engineers, analysts, and business stakeholders

Required Skills:

• Strong experience with Databricks, Spark, PySpark, and SQL
• Hands-on experience with AWS cloud services (S3, Glue, Redshift, EMR, Lambda)
• Experience in building data pipelines and data warehousing solutions
• Knowledge of CI/CD, Git, and Agile methodologies
• Good communication and problem-solving skills

Nice to Have:

• Experience with Delta Lake, MLflow, or Lakehouse architecture
• Exposure to Airflow, Kafka, or streaming data pipelines

Note: Gurgaon location mandatory. Immediate joiners preferred.

Please share updated CV to