Description

Build and maintain scalable data pipelines and storage solutions on cloud platforms.

This role is on-site.

Responsibilities

• Design and implement ETL/ELT workflows using Python and SQL.
• Develop distributed processing jobs with Spark or PySpark.
• Manage data warehouses including Redshift, Snowflake, BigQuery, or Synapse.
• Deploy and monitor data workflows using CI/CD pipelines and orchestration tools like Airflow or Azure Data Factory.
• Ensure data security, encryption, and access controls across AWS, Azure, or GCP environments.

Required Skills

• 8+ years of experience in data engineering and processing.
• Strong proficiency in Python and SQL (mandatory).
• Hands-on experience with distributed processing frameworks (Spark/PySpark).
• Deep knowledge of relational databases: PostgreSQL, Oracle, MySQL, SQL Server.
• Experience with cloud data warehouses: Redshift, Snowflake, BigQuery, Synapse.
• Proficiency with cloud platforms (AWS or Azure preferred) and storage (S3, ADLS, GCS).
• Familiarity with Git/GitHub and workflow orchestration tools.
• Experience working in Agile/Scrum environments.

Preferred Skills

• Exposure to NoSQL databases.
• Knowledge of data governance, lineage, and metadata management.
• Experience in regulated or enterprise environments with data quality frameworks.

Key Skills

Education

Any Gradute