Key Responsibilities

- Lead the development of scalable, high-performance data pipelines using PySpark or Big Data ETL pipeline technologies.
- Drive data modelling efforts for analytics, dashboards, and knowledge graphs.
- Oversee the implementation of parquet-based data lakes.
- Work on OLAP databases, ensuring optimal data structure for reporting and querying.
- Architect and optimize large-scale enterprise big data implementations with a focus on modular and reusable low-code libraries.
- Collaborate with stakeholders to design and deliver AI and DWH solutions that align with business needs.
- Mentor and lead a team of engineers, building out the data and AI services organization.

Requirements

- 8 + years of experience in big data and AI technologies, with expertise in PySpark or similar Big Data ETL pipeline technologies.
- Experience with AWS & services like EMR.
- Familiarity with Iceberg, Dremio tools




- Strong proficiency in SQL and OLAP database technologies.
- Firsthand experience with data modeling for analytics, dashboards, and knowledge graphs.
- Proven experience with parquet-based data lake implementations.
- Expertise in building highly scalable, high-volume data pipelines.
- Experience with modular, reusable, low-code-based implementations.
- Involvement in large-scale enterprise big data implementations.
- Initiative-taker with strong motivation and the ability to lead a growing team.

Preferred

- Experience leading a team or building out a recent department.
- Experience with cloud-based data platforms and AI services.
- Familiarity with supply chain technology or fulfilment platforms is a plus.

📌 Data Architect (Chennai)
🏢 Pando
📍 Chennai