About this role
Position: Data Engineer with Power BI - Senior engineer (Level 1)
Job Description: Key Responsibilities • Design, develop, and maintain interactive dashboards, reports, and semantic models using Power BI. • Create optimized data models, DAX calculations, KPIs, measures, Power Query transformations, and enterprise reporting solutions. • Develop and maintain complex SQL queries, stored procedures, and database objects for analytics and reporting. • Build and maintain scalable ETL/ELT pipelines using AWS Glue, Amazon EMR, AWS Lambda, or similar AWS data integration services. • Develop Python scripts for automation, data processing, validation, and workflow optimization. • Integrate data from multiple enterprise systems including SQL Server, Oracle, SAP, ERP, APIs, AWS services, and cloud data warehouses. • Work with modern cloud platforms including AWS, Amazon Redshift, Amazon S3, Databricks, and Power BI. • Design dimensional data models (Star Schema/Snowflake Schema) and publish curated datasets for enterprise analytics. • Optimize Power BI reports through DAX optimization, query tuning, incremental refresh, aggregation, and performance best practices. • Implement Row-Level Security (RLS), workspace governance, deployment pipelines, and Power BI Service administration. • Collaborate with Data Engineering teams to design scalable data lake, Lakehouse, and Medallion Architecture solutions. • Support deployment, release management, CI/CD implementation, and migration across Development, UAT, and Production environments. • Maintain technical documentation for dashboards, datasets, pipelines, and operational runbooks. • Troubleshoot reporting, performance, data quality, and production issues while ensuring high availability of analytics solutions. • Work closely with business stakeholders to gather reporting requirements and translate them into scalable technical solutions. Primary Skills (Must Have) Power BI & Analytics • Strong hands-on experience developing enterprise Power BI reports, dashboards, and semantic models. • Expertise in DAX, Power Query (M), calculated measures, calculated columns, relationships, and data modeling. • Experience publishing and managing datasets using Power BI Service. • Knowledge of Row-Level Security (RLS), Incremental Refresh, Gateways, Deployment Pipelines, Workspace Management, and report performance optimization. • Experience building executive dashboards, KPI scorecards, and self-service BI solutions. Programming Languages • Advanced SQL (essential) for query optimization, stored procedures, and analytics. • Strong Python programming for automation, data processing, scripting, and ETL development. Data Engineering & ETL • Hands-on experience building ETL/ELT pipelines using AWS Glue, Amazon EMR, AWS Lambda, Amazon Kinesis, or similar AWS services. • Experience working with Amazon S3 as a data lake. • Knowledge of data orchestration, monitoring, and workflow automation using AWS services. • Understanding of Medallion Architecture, Lakehouse concepts, and modern data engineering best practices. Data Warehousing & Cloud Platforms • Experience with AWS (Redshift, S3, Glue, Athena, EMR, Lambda, IAM, CloudWatch). • Experience with Databricks, or equivalent cloud data platforms. • Strong understanding of cloud data warehousing, Lakehouse architecture, and dimensional modeling Data Modeling & Database • Strong understanding of Star Schema, Snowflake Schema, and dimensional modeling. • Experience working with SQL Server, Oracle, MySQL, DynamoDB or cloud databases. • Knowledge of semantic modeling and enterprise reporting architecture. Engineering Best Practices • Experience using Git/version control. • Experience implementing CI/CD pipelines • Familiarity with Agile/Scrum methodologies. • Strong documentation, troubleshooting, and code review practices. Data Governance & Security • Experience implementing security using AWS IAM, encryption, secrets management, and data governance best practices. • Knowledge of data privacy, RBAC and secure data sharing. Secondary Skills (Good to Have) • Exposure to other cloud analytics platforms such as Azure, Snowflake Qualification • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. • 5–8 years of experience in Power BI, Data Analytics, and Data Engineering. • Strong analytical, troubleshooting, communication, and stakeholder management skills. • Ability to work effectively with cross-functional business and technical team. Preferred Certifications • Microsoft Power BI Data Analyst Associate • AWS Certified Data Engineer – Associate or AWS Certified Solutions Architect – Associate • AWS Certified Developer – Associate • Databricks Fundamentals or Associate Certification Tools & Technologies • Power BI Desktop & Power BI Service • Amazon S3 • AWS Glue • Amazon Redshift • Amazon Athena • Amazon EMR • AWS Lambda • Amazon Kinesis • AWS IAM & CloudWatch • SQL Server / Oracle / MySQL / DynamoDB • Python • Advanced SQL • DAX & Power Query • Git / GitHub / AWS CodePipeline / Jenkins
Location: IN-MH-Pune, India-Blue Ridge-Hinjewadi (eInfochips)
Time Type: Full time
Job Category: Engineering Services