Description

You will build and maintain data infrastructure to support analytics and machine learning workloads.

This role is on-site.

Responsibilities

• Design, build, and maintain ETL/ELT workflows using Databricks.
• Develop scalable data pipelines utilizing Python and Spark.
• Optimize data transformation logic for performance and cost efficiency.
• Develop and manage data models, schemas, and tables across SQL and NoSQL databases.
• Implement data quality, validation, and monitoring frameworks for pipelines.

Required Skills

• 5+ years of professional experience in data engineering.
• Expertise in Databricks, including Delta Lake, Notebooks, Spark SQL, Jobs, and Workflows.
• Strong proficiency in Python for data processing, Spark APIs, and automation.
• Deep understanding of SQL, query tuning, and schema design for database engineering.
• Experience with Apache Spark (RDDs/DataFrames, optimization, partitioning).
• Familiarity with CI/CD practices using Git, DevOps, or Jenkins.
• Experience integrating data from APIs, streaming sources, and cloud storage.
• Knowledge of ETL/ELT tools (ADF, Glue, Dataflow, or equivalent).

Key Skills

Education

Any Gradute