Enterprise Data Warehouse (EDW) Engineer – Hyderabad (Onsite)

About the Role

We are seeking a Mid-Level Enterprise Data Warehouse (EDW) Engineer with a passion for building scalable, cloud-native data solutions. This position is ideal for individuals who excel in collaborative environments, communicate effectively, and approach challenges with a problem-solving mindsetnot just those who follow instructions.

Key Responsibilities

• Design, develop, and maintain high-performance data pipelines and ETL/ELT workflows for the enterprise data warehouse.
• Work with cloud-based data warehouse platforms like Snowflake, BigQuery, or Redshift to optimize data storage and retrieval.
• Write clean, efficient, and maintainable SQL and Python code for data transformation and automation tasks.
• Implement and manage CI/CD pipelines for data workflows using tools like Git, Jenkins, or GitHub Actions.
• Leverage orchestration tools (e.g., Apache Airflow, dbt Cloud, Prefect) to schedule and monitor data workflows.
• Conduct detailed data analysis between current and target systems, and prepare mapping documentation.
• Collaborate with data analysts, scientists, and business teams to generate actionable insights.
• Proactively identify and address data quality issues and performance bottlenecks.
• Contribute to data architecture decisions and establish best practices.

Required Qualifications

• 4-15 years of experience in Data Engineering or EDW Development.
• Strong hands-on experience with Snowflake, BigQuery, or Redshift.
• Expertise in SQL and Python.
• Working knowledge of CI/CD tools such as Git, Jenkins, and GitHub Actions.
• Experience with workflow orchestration tools like Airflow and Prefect.
• Ability to analyze large datasets and present findings in a business context.
• Excellent communication and teamwork skills.
• A proactive, solution-oriented mindset with strong ownership and accountability.

Preferred Qualifications

• Experience in data modeling and architecture.
• Understanding of data governance, security, and compliance best practices.
• Familiarity with modern data stack tools such as dbt, Fivetran, or Looker.
• Experience with large-scale enterprise data warehouse implementations.