Description

You will design, build, and maintain scalable data pipelines and Lakehouse architectures using Databricks and PySpark. This role is on-site.

Responsibilities

• Develop and optimize ETL/ELT workflows for structured and semi-structured data using PySpark and SQL.
• Build and manage Delta Lake tables and implement Lakehouse architecture patterns.
• Optimize Spark applications for performance, scalability, and cost efficiency.
• Create and maintain Databricks notebooks, jobs, and automated workflows.
• Ensure data quality, governance, and security standards across the platform.

Required Skills

• Strong experience with Databricks, Apache Spark, and PySpark (5+ years).
• Proficiency in SQL and Python for data engineering tasks.
• Hands-on experience with Delta Lake and Lakehouse architecture.
• Experience building ETL/ELT pipelines and data transformation workflows.
• Knowledge of cloud platforms (Azure, AWS, or GCP), specifically AWS Databricks.
• Understanding of Data Warehousing and Data Modeling concepts.
• Experience with Git, CI/CD, and DevOps practices.

Preferred Skills

• Databricks Certification (Associate/Professional).
• Experience with Azure Data Factory, Synapse, Kafka, or Airflow.
• Knowledge of Unity Catalog and data governance frameworks.

Key Skills

Education

Any Graduate