Senior Snowflake Developer.

Job Title: Senior Snowflake Developer (dbt & Delta Processing Specialist)

Duration : Long Term

• Data Pipeline & Architecture: Design, develop, and maintain robust, scalable ETL/ELT pipelines within Snowflake using SQL, Python, and modern data stack tools.
• dbt Transformation Layer: Architect and manage the dbt environment (dbt Core or dbt Cloud). Write modular, highly optimized dbt models, macros, and tests, ensuring clean data lineage and documentation.
• CDC & Ingestion: Implement and optimize continuous data ingestion and Change Data Capture (CDC) mechanisms from various source systems (Transactional DBs, SaaS APIs) into Snowflake using tools like Snowflake Pipes (Snowpipe), Streams, Tasks, or external replication tools (e.g., Fivetran, Debezium, Qlik).
• Delta & Incremental Processing: Design efficient Delta processing architectures utilizing dbt incremental models, Snowflake Streams, and merge strategies to process only modified or new data, minimizing compute costs and latency.
• Performance Tuning: Optimize complex SQL queries, dbt models, clustering keys, and virtual warehouse configurations to ensure optimal query performance and cost-efficiency.
• Data Governance & Quality: Implement automated data quality checks, data masking, row-level security, and role-based access control (RBAC) within Snowflake.

• Snowflake Expertise: Deep understanding of Snowflake architecture (Cloud Services, Virtual Warehouses, Storage), semi-structured data handling (JSON, Parquet), Time Travel, Zero-Copy Cloning, and Snowpark.
• Advanced dbt: Proven experience with dbt engineering, including complex macro development, incremental model strategies, package management, and performance tuning at scale.
• CDC & Stream Processing: Hands-on experience capturing real-time or near-real-time source changes using Snowflake Streams & Tasks, Kafka, or log-based CDC tools.
• Delta Processing & Handling: Strong grasp of delta logic, idempotency, slowly changing dimensions (SCD Type 1/2/4), and transaction handling.
• Languages: Expert-level SQL proficiency (analytical functions, window functions, query optimization) and solid experience with Python for data processing.
• Cloud Platforms: Experience working with cloud ecosystems (AWS, Azure, or Google Cloud Platform) and managing external stages.
• DevOps for Data: Familiarity with Git, CI/CD pipelines (GitHub Actions, GitLab CI) for deploying dbt code and Snowflake schema changes (e.g., using Schemachange or dbt commands).

• Snowflake Certified Data Engineer (or Advanced Certified).
• Experience migrating legacy ETL workflows (e.g., Informatica, Talend, stored procedures) into Snowflake/dbt.
• Experience with Iceberg tables or Databricks Delta Lake integration with Snowflake.

Thanks & Regards,

Subash – US IT Consulting