Senior Snowflake Developer | Snowflake DW, Advanced SQL, Python

Job description

• Design, develop, and maintain scalable Snowflake Data Warehouse (DW) solutions to support business and analytics requirements. • Build and optimize ETL/ELT pipelines for ingesting, transforming, and loading data from multiple source systems into Snowflake. • Develop and tune complex SQL queries, stored procedures, tasks, streams, and views to ensure high performance and efficient data processing. • Implement and manage Snow pipe, stages, and continuous data ingestion frameworks for real-time and batch data loading. • Work with structured and semi-structured data (JSON, XML, Parquet, Avro) and develop scalable data transformation solutions. • Design and implement data models including Star Schema, Snowflake Schema, Dimensions, and Fact Tables. • Collaborate with architects, data engineers, analysts, and business stakeholders to understand requirements and deliver data solutions. • Develop automation and scripting solutions using Python (or Scala) for data processing, orchestration, validation, and monitoring. • Integrate Snowflake with cloud platforms and services such as AWS S3, Kafka, and other enterprise data sources. • Monitor, troubleshoot, and optimize Snowflake workloads, warehouses, caching mechanisms, and overall platform performance. • Implement data governance, data quality, security, RBAC, masking policies, and compliance controls across the Snowflake ecosystem. • Perform data validation, reconciliation, and completeness checks to ensure accurate and reliable data delivery. • Support data migration initiatives and resolve challenges associated with migrating legacy data warehouse workloads to Snowflake. • Leverage advanced Snowflake capabilities such as Time Travel, Fail-safe, Data Sharing, Dynamic Tables, Cortex AI/ML, and Zero-Copy Cloning where applicable. • Participate in architecture discussions, code reviews, and best practice adoption to ensure scalable and maintainable data solutions. • Create technical documentation, operational runbooks, and deployment procedures while providing production support and issue resolution. Preferred candidate profile • 4 to 10 years of overall IT experience with at least 3+ years of hands-on experience in Snowflake Data Warehouse. • Strong expertise in Advanced SQL, query optimization, stored procedures, views, tasks, streams, and window functions. • Solid understanding of Data Warehousing concepts, dimensional modeling, Star/Snowflake schemas, SCD implementation, and ETL/ELT frameworks. • Proven experience designing and implementing large-scale data pipelines and data integration solutions on Snowflake. • Hands-on experience with Snowflake features such as Snow pipe, Time Travel, Zero-Copy Cloning, Dynamic Tables, Data Sharing, RBAC, and Data Masking. • Strong programming skills in Python (preferred) or Scala for automation, data processing, and orchestration. • Experience working with semi-structured data such as JSON, XML, Parquet, and Avro. • Good knowledge of streaming technologies such as Kafka and real-time data ingestion patterns. • Experience with cloud storage platforms such as AWS S3 and cloud-native data architectures. • Strong understanding of Data Governance, Data Quality, Security, and Compliance practices. • Experience in performance tuning, troubleshooting, and optimizing Snowflake workloads and warehouses. • Exposure to AI/ML capabilities within Snowflake, including Snowflake Cortex, will be an added advantage. • Excellent problem-solving, communication, and stakeholder management skills. • Ability to work in a fast-paced, cross-functional, and client-facing environment.