Power BI / Data Analytics Engineer

Job Description:

Job Summary

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, and technical processes.
• Troubleshoot reporting, data quality, and performance-related issues.
• Participate in CI/CD implementation, version control, and DevOps best practices for BI and analytics solutions.
• Work closely with business users and stakeholders to gather reporting requirements and translate them into technical solutions.

Primary Skills

• Programming Languages
• Advanced SQL (essential) for query optimization, data transformation, and database development.
• Python for scripting, automation, and data processing.
• BI & Visualization Tools
• Strong hands-on experience in Power BI.
• Experience with Tableau or Looker is an added advantage.
• Expertise in DAX, Power Query (M Language), and data modeling concepts.
• Data Warehouses & Cloud Platforms
• Experience with Snowflake, Google BigQuery, AWS Redshift, or Microsoft Azure.
• Knowledge of cloud analytics and modern data warehouse architecture.
• Transformation & ETL Tools
• Experience with dbt (Data Build Tool), Fivetran, Apache Airflow, or similar ETL/ELT tools.
• Strong understanding of data integration and orchestration processes.
• Data Engineering & Database Skills
• Strong understanding of data warehousing concepts, star/snowflake schema, and dimensional modeling.
• Experience working with SQL Server, Oracle, MySQL, or cloud databases.
• Knowledge of ETL/ELT pipeline development and data transformation best practices.
• Engineering Best Practices
• Experience with Git/version control systems.
• Knowledge of CI/CD pipelines, deployment automation, and DevOps practices.
• Familiarity with Agile/Scrum development methodologies

Secondary Skills (Good to Have)

• Experience with Databricks, PySpark, and Spark SQL.
• Exposure to Azure Data Factory, Azure Synapse Analytics, and Microsoft Fabric.
• Knowledge of lakehouse architecture and big data processing concepts.
• Experience integrating ERP systems such as SAP, JDE, or enterprise applications.
• Understanding of API integrations and data exchange frameworks.
• Exposure to cloud-native analytics and AI-enabled reporting solutions.

Qualification

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field.
• 4–6 years of experience in Power BI and BI reporting solutions.
• Good analytical, troubleshooting, and communication skills.
• Ability to work with cross-functional business and technical teams.
• Preferred Certifications
• Microsoft Power BI Data Analyst Associate
• Azure Data Engineer Associate
• Snowflake SnowPro Certification
• Databricks Fundamentals or Associate Certification

Tools & Technologies