Data Engineer (Mid To Senior Level) _ Up To 30LPA

Immediate Joiners Only!!!

4 - 15 Years of experienced candidates!!

Salary Range - 8 - 30 LPA with Perks including Joining Bonus, Insurance and more!

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 role is ideal for someone who thrives in a collaborative environment, communicates effectively, and brings a problem-solving mindset to every challenge, not just someone who takes orders.

Key Responsibilities

• Design, develop, and maintain robust data pipelines and ETL/ELT processes for our enterprise data warehouse.
• Work with cloud-based data warehouse platforms (e.g., Snowflake, BigQuery, Redshift) to manage and optimize data storage and retrieval.
• Write efficient, maintainable, and well-documented SQL and Python code for data transformation and automation.
• Implement and maintain CI/CD pipelines for data workflows, ensuring smooth deployment and version control.
• Use orchestration tools (e.g., Apache Airflow, dbt Cloud, Prefect, etc.) to schedule and monitor data workflows.
• Perform deep data analysis between current state and future state systems, produce mapping documents.
• Collaborate with cross-functional teams including data analysts, data scientists, and business stakeholders to understand data needs and deliver actionable insights.
• Proactively identify data quality issues and performance bottlenecks, and implement solutions.
• Contribute to architectural decisions and best practices for data engineering and warehousing.

Required Qualifications

• Minimum 4 to 15 years of experience in data engineering or enterprise data warehouse development.
• Hands-on experience with cloud data warehouse platforms (e.g., Snowflake, BigQuery, Redshift).
• Strong proficiency in SQL and Python for data manipulation and automation.
• Solid understanding of CI/CD concepts and experience with tools like Git, Jenkins, or GitHub Actions.
• Experience with workflow orchestration tools such as Airflow, Prefect, or similar.
• Must be able to independently analyze large datasets and connect the dots with the business processes.
• Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders.
• A proactive, problem-solving mindsetsomeone who takes initiative and drives solutions.

Preferred Qualifications

• Experience with data modeling and data architecture principles.
• Familiarity with data governance, security, and compliance best practices.
• Experience working with modern data stack tools like dbt, Fivetran, or Looker.
• Experience working in large scale Enterprise Data Warehouse implementations.