Key Responsibilities:

- Assist in building and maintaining scalable data pipelines using tools like PySpark and SQL-based ETL processes.
- Support the development and maintenance of data models for dashboards, analytics, and reporting.
- Help manage parquet-based data lakes and ensure data consistency and quality.
- Write optimized SQL queries for OLAP database systems and support data integration efforts.
- Collaborate with team members to understand business data requirements and translate them into technical implementations.
- Document workflows, data schemas, and data definitions for internal use.
- Participate in code reviews, team meetings, and training sessions to continuously improve skills.

Requirements:

- 2–4 years of experience working with data engineering or ETL tools (e.g., PySpark, SQL, Airflow).




- Solid understanding of SQL and basic experience with OLAP or data warehouse systems.
- Exposure to data lakes, preferably using Parquet format.
- Understanding of basic data modeling principles (e.g., star/snowflake schema).
- Valuable problem-solving skills and willingness to learn and adapt.
- Ability to work effectively in a collaborative, fast-paced team environment.

Preferred Qualifications:

- Experience working with cloud platforms (AWS, Azure, or GCP).
- Exposure to low-code data tools or modular ETL frameworks.
- Interest or prior experience in the supply chain or logistics domain.
- Familiarity with dashboarding tools like Power BI, Looker, or Tableau.

📌 Data Warehouse Engineer (Chennai)
🏢 Pando
📍 Chennai