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Full Stack Analytics Engineer/ Data Engineer (Snowflake, Python, dbt, Tableau)

Job Description - Full Stack Analytics Engineer/ Data Engineer (Snowflake, Python, dbt, Tableau)

Description
  • 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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