Description

You will build and maintain scalable ETL/ELT pipelines using Apache Spark and Snowflake.

This role is on-site.

Responsibilities

• Design and develop data processing, transformation, and analytics workflows in distributed environments using Databricks.
• Implement data warehousing solutions in Snowflake, focusing on performance, cost, and security.
• Write efficient SQL and Spark applications to process large-scale datasets from cloud storage, APIs, and RDBMS.
• Ensure data quality and integrity through unit testing, validation, and monitoring.
• Optimize and troubleshoot Spark jobs, SQL queries, and Snowflake workflows.

Required Skills

• 3+ years of experience with Snowflake, including schema design, query optimization, and Snowpipe, Streams, or Tasks.
• 2+ years of hands-on development with Apache Spark using PySpark, Scala, or Java.
• Proficiency in SQL and Spark (RDD/DataFrame APIs).
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with data modeling, data quality, and orchestration tools like Airflow or DBT.
• Knowledge of CI/CD pipelines and version control using Git or GitHub Actions.
• Understanding of distributed computing, data lakes, and modern data architectures.

Preferred Skills

• Experience with Prefect for orchestration.

Key Skills

Education

Any Graduate