Description

Key Responsibilities:
Design and implement scalable data lake/lakehouse architectures on AWS using S3 and Iceberg.
Develop and optimize ETL/ELT pipelines using PySpark and orchestrate workflows with Apache Airflow.
Integrate and manage Snowflake as the enterprise data warehouse and business layer for analytics.
Ensure data quality, governance, security, and performance across the data platform.
Lead technical design discussions, define best practices, and drive data engineering standards.
Mentor and guide a team of data engineers, fostering a collaborative and high-performance culture.
Collaborate with cross-functional teams including data analysts, data scientists, and business stakeholders.

Responsibilities
Key Responsibilities:
Design and implement scalable data lake/lakehouse architectures on AWS using S3 and Iceberg.
Develop and optimize ETL/ELT pipelines using PySpark and orchestrate workflows with Apache Airflow.
Integrate and manage Snowflake as the enterprise data warehouse and business layer for analytics.
Ensure data quality,



governance, security, and performance across the data platform.
Lead technical design discussions, define best practices, and drive data engineering standards.
Mentor and guide a team of data engineers, fostering a team-oriented and high-performance culture.
Collaborate with cross-functional teams including data analysts, data scientists, and business stakeholders.

Qualifications
Required Skills & Qualifications:
9+ years of experience in data engineering or related roles.
Proven expertise in AWS services, especially S3-based data architectures.
Robust hands-on experience with Apache Iceberg, PySpark, and Apache Airflow.
Solid experience implementing Snowflake as a data warehouse/business layer.
Solid programming skills in Python and distributed data processing frameworks.
Experience leading and mentoring engineering teams.
Excellent problem-solving, communication, and collabo

📌 Lead Aws Data Engineer Pune
🏢 EXL
📍 Pune