Sr. Data Engineer / Sr. BI Developer

Job Summary

Sr. Data Engineer/Sr. BI Developer in the Health Care domain responsible for designing, developing, and supporting enterprise-grade data platforms and analytics solutions using Snowflake, dbt, and modern data engineering practices.

Candidate must have relevant experience of 5 to 7 Years.

The role focuses on building scalable ELT pipelines, implementing Medallion Architecture (Bronze/Silver/Gold), enabling advanced analytics and AI-driven insights, and ensuring robust data quality, governance, and performance across production environments.

Key Responsibilities

• Design, develop, and support enterprise data platforms on Snowflake, including data modeling and Medallion Architecture (Bronze/Silver/Gold) for healthcare data and analytics use cases.
• Build and maintain scalable ELT pipelines for batch and real-time data ingestion using Snowflake capabilities such as Snowpipe, Snowpipe Streaming, Streams, Tasks, Dynamic Tables, and Snowpark.
• Implement and manage CDC frameworks to support near real-time data synchronization across systems.
• Lead data migration initiatives to Snowflake, ensuring data integrity, performance, and minimal downtime.
• Optimize Snowflake query and warehouse performance, including clustering, caching, and resource utilization tuning.
• Implement secure data movement across systems and environments, ensuring adherence to data governance and compliance standards within the healthcare domain.
• Leverage advanced Snowflake capabilities such as Streamlit, Cortex Intelligence, Cortex Analyst, Cortex Search, and AI-driven analytics solutions to deliver advanced reporting and insights.
• Design and develop dbt models across staging, intermediate, and marts layers with strong dimensional modeling practices.
• Build reusable transformation frameworks, incremental models, snapshots, and robust data quality tests in dbt.
• Implement incremental strategies in dbt such as Merge, Append, Insert Overwrite, and Delete + Insert to efficiently process large datasets.
• Develop custom macros and Jinja templates in dbt to standardize transformations and enforce best practices.
• Manage lineage and documentation in dbt, ensuring transparency and traceability of data flows.
• Handle CI/CD deployments for dbt projects, including Git-based development workflows, code reviews, and automated testing.
• Migrate legacy ETL processes to dbt-based ELT frameworks, ensuring improved maintainability, scalability, and performance.
• Implement and maintain SCD Type 1 and Type 2 patterns within dbt models for slowly changing dimensions.
• Use orchestration tools such as Airflow, Azure Data Factory (ADF), or dbt Cloud to schedule, monitor, and manage production-grade data workflows.
• Collaborate with data analysts, BI developers, and business stakeholders to translate healthcare data requirements into scalable data models and reporting solutions.
• Ensure high standards of data quality, reliability, and observability across all data pipelines and models.
• Troubleshoot and resolve production issues related to data pipelines, models, and performance in a timely manner.
• Contribute to continuous improvement by adopting best practices in Data Automation & AI, Data Engineering, and analytics engineering.