- Job Description: The ideal candidate will have strong expertise in Snowflake , Hadoop ecosystem , PySpark , and SQL , and will play a key role in enabling data-driven decision-making across the organization.

- Responsibilities: Design, develop, and optimize robust data pipelines using PySpark and SQL.

- Implement and manage data warehousing solutions using Snowflake.

- Work with large-scale data processing frameworks within the Hadoop ecosystem.

- Collaborate with data scientists, analysts, and business stakeholders to understand data requirements.

- Ensure data quality, integrity, and governance across all data platforms.

- Monitor and troubleshoot data pipeline performance and reliability.

- Automate data workflows and implement best practices for data engineering.

- Qualifications:



5+ years of experience in data engineering or related roles.

- Solid hands-on experience with Snowflake including data modeling, performance tuning, and security.

- Knowledge in PySpark for distributed data processing.

- Solid understanding of Hadoop ecosystem (HDFS, Hive, Spark, etc.).

- Advanced SQL skills for data manipulation and analysis.

- Experience with ETL tools and orchestration frameworks (e.g., Airflow, DBT).

- Familiarity with cloud platforms (AWS, Azure, or GCP) is a plus.

- Excellent problem-solving and communication skills.

📌 Lead Assistant Manager-Data Engineering-Cloud Data Engineering (India)
🏢 EXL Service
📍 India