Design, develop, and optimize data pipelines using PySpark and SQL; manage Snowflake data warehouses; process large-scale data through the Hadoop ecosystem; and ensure data quality, governance, performance, and reliability. The role also automates workflows, uses ETL and orchestration tools, and collaborates with data scientists, analysts, and business stakeholders.
- 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.
- 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.
- 5+ years of experience in data engineering or related roles.
- Strong 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.
EXL Chennai, Tamil Nadu, IND Office
Chennai, India
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