Padmi

Power BI (Ahmedabad)

IndiaPosted 1 month ago
Software engineeringMid-levelFull Time; Regular
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Position: Power BI / Data Analytics Engineer Job Description: Position : Power BI / Data Analytics Engineer Job Summary We are looking for a skilled and detail-oriented Power BI / Data Analytics Engineer with 46 years of experience in business intelligence, data engineering, and cloud analytics platforms. The candidate will be responsible for designing, developing, and maintaining scalable BI solutions, automated data pipelines, and interactive dashboards to support business decision-making. The ideal candidate should have strong expertise in Power BI, Advanced SQL, and Python, along with experience in contemporary cloud data platforms, ETL/ELT tools, and data transformation frameworks. The role requires close collaboration with business stakeholders, data engineers, architects, and analytics teams in a fast-paced environment. Key Responsibilities - Design, develop, and maintain interactive dashboards and reports using Power BI, Tableau, or Looker. - Create optimized data models, DAX calculations, KPIs, and measures for enterprise reporting solutions. - Develop and maintain complex SQL queries, stored procedures, and database objects for analytics and reporting. - Use Python for scripting, automation, data processing, and workflow optimization. - Build and manage ETL/ELT pipelines using dbt, Fivetran, Airflow, or similar transformation tools. - Integrate data from multiple sources including SQL Server, Oracle, SAP, APIs, cloud platforms, and enterprise applications. - Work with cloud data warehouses such as Snowflake, Google BigQuery, AWS Redshift, and Microsoft Azure platforms. - Collaborate with data engineering teams to design scalable and efficient data pipelines and analytics solutions. - Implement report optimization, performance tuning, row-level security (RLS), and governance standards. - Support deployment, release management, and migration activities across Dev, UAT, and Production environments. - Maintain documentation for dashboards, datasets, pipelines, .

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