Snowflake Data Eng + MCP

Job description

**Job Description: Data Engineer (Snowflake, Custom MCPs, SQL, Python,** **dbt)** Experiece:5-10Years Locations: PAN India **Role Overview** We are looking for a skilled Data Engineer with strong expertise in Snowflake, custom MCP (Modular Compute Pipelines/Custom Processing frameworks), SQL, Python, and dbt. The role focuses on building scalable, modular, and high-performance data pipelines, data models, and transformation frameworks on Snowflake. The engineer will design reusable components (MCPs), ensure efficient data processing, and enable analytics and downstream consumption. **Key Responsibilities** - Design and develop scalable data pipelines and transformation frameworks on Snowflake. - Build and manage custom MCPs (Modular Compute Pipelines or reusable data processing components) for standardized data processing. - Develop robust SQL-based transformations and optimize complex queries in Snowflake. - Implement and manage dbt models, macros, tests, and documentation for data transformation workflows. - Develop data processing scripts using Python for orchestration, enrichment, and integration tasks. - Ensure data quality, validation, and reconciliation using automated checks and dbt testing frameworks. - Perform performance tuning and cost optimization in Snowflake (clustering, partitioning, warehouse sizing). - Integrate data pipelines with orchestration tools such as Airflow or native schedulers. - Collaborate with data architects, analysts, and business stakeholders to design scalable data models. - Maintain documentation, lineage, and governance for data assets. **Mandatory Skills** - Strong hands-on experience with Snowflake data platform and architecture. - Expertise in SQL for data transformation, modeling, and performance optimization. - Proficiency in Python for data engineering and automation tasks. - Hands-on experience with dbt (models, macros, tests, snapshots). - Experience in designing reusable data components (custom MCP frameworks or modular pipelines). - Strong understanding of ETL/ELT concepts and data warehousing principles. - Experience with performance tuning and cost optimization techniques in Snowflake. - Familiarity with version control systems (Git) and CI/CD processes. **Preferred Skills** - Experience with orchestration tools like Apache Airflow, Prefect, or similar. - Knowledge of cloud platforms such as AWS, Azure, or GCP. - Experience with data governance, lineage, and metadata management. - Exposure to streaming frameworks and real-time data processing. - Understanding of data security, access control, and compliance best practices. - Certifications in Snowflake or dbt are a plus. **Soft Skills** - Strong analytical and problem-solving skills. - Effective communication and stakeholder management. - Ability to work in a fast-paced and data-driven environment. - Strong ownership and proactive approach to problem resolution. **Key Deliverables / Success Metrics** - High-performance, scalable Snowflake data pipelines. - Reusable MCP frameworks improving engineering productivity. - Well-documented dbt models with high test coverage. - Optimized Snowflake cost and performance. - Reliable and high-quality datasets for downstream analytics.