About the role
- Design, develop, and maintain scalable data transformation and analytics pipelines using Snowflake, SQL, Python, and dbt. - Perform data extraction, cleansing, preprocessing, validation, and transformation from multiple data sources. - Develop complex and optimized SQL queries, stored procedures, views, and data models in Snowflake. - Build and maintain dbt models, macros, tests, snapshots, and documentation following analytics engineering best practices. - Use Python for data preprocessing, automation, data validation, and analytical workflows. - Develop and maintain Tableau dashboards, reports, visualizations, and KPI reporting for business stakeholders. - Translate business requirements into effective data models, metrics, dashboards, and analytical solutions. - Perform data profiling and quality checks to ensure accuracy, completeness, consistency, and reliability of reporting data. - Optimize SQL queries, Snowflake workloads, dbt models, and Tableau dashboards for performance. - Collaborate with Business Analysts, Data Engineers, Data Scientists, and business stakeholders to understand reporting and analytics requirements. - Troubleshoot data and reporting issues and provide root-cause analysis. - Establish reusable data transformation and reporting frameworks to improve scalability and maintainability. - Ensure proper documentation of data sources, transformations, business rules, and reporting logic.
Requirements
- 6+ years of overall experience in Analytics Engineering, Data Engineering, BI, or a related role. - Strong hands-on experience with Snowflake and advanced SQL. - Strong Python experience for data preprocessing, transformation, automation, and validation. - Hands-on experience with dbt for data transformation and analytics engineering. - Strong experience in Tableau dashboard and report development. - Experience working across data preprocessing → transformation → data modeling → BI reporting. - Strong understanding of ETL/ELT concepts, dimensional modeling, and data warehousing. - Good understanding of data quality, governance, and performance optimization. - Strong analytical and problem-solving skills with the ability to work directly with business stakeholders.
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