Big Data Lead - Snowflake & AWS

Job Title: Big Data Lead / ETL Developer

Interested : https://forms.office.com/r/sU5bhsquHS or share resume @ VimalaP3@hexaware.com

• Design, build, and maintain ETL/ELT pipelines using IICS to ingest, transform, and load data into Snowflake.
• Leverage Snowflake native data load services (Stages, Snowpipe, Streams, Tasks) to implement efficient ingestion patterns.
• Optimize Snowflake storage and query performance using clustering, micro-partitioning, materialized views, and query tuning.
• Develop advanced SQL solutions, analytical queries, stored procedures, and materialized views to support analytics and reporting.
• Implement data security best practices and role-based access controls for sensitive datasets.
• Monitor pipeline reliability and data quality; implement alerts, logging, and automated remediation where possible.
• Collaborate with data analysts, data scientists, product owners, and other engineering teams to deliver production-ready datasets.
• Maintain CI/CD and version control for ETL jobs, including deployment automation and runbooks.
• Document data models, pipeline designs, SLAs, and operational procedures.

Must Have

• Proficient in Snowflake with hands-on experience leveraging native data load services of Snowflake.
• Exceptional expertise in SQL, advanced SQL, analytical functions, materialized views, and stored procedures.
• Knowledge in Snowflake data loading features like Stages, Streams, Tasks, and Snowpipe.
• Working knowledge on IICS with at least 3 years of experience.
• Strong analytical skills.
• Expertise in one of the major cloud platforms (AWS, Azure, or GCP) is a must.
• Proven experience building and optimizing data pipelines, architectures, and datasets.

Nice to Have

• Experience in Python for transformations, orchestration, or automation.
• Knowledge of modern DevOps practices including Git, CI/CD, and Azure DevOps/VSTS.
• Experience with business intelligence tools (Tableau, Power BI, Looker, etc.).
• Familiarity with data testing/quality frameworks (Great Expectations, dbt tests, etc.).
• Understanding of data lake patterns, Parquet/ORC formats, and cloud cost optimization.