About this role
• 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.