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Power BI / AWS Data Engineer – Job Description

Position :  Power BI and AWS Data Engineer

Job Summary

We are looking for a skilled and detail-oriented Power BI / AWS Data Engineer with 4–6 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, Python, and AWS cloud data services, along with experience in modern 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, 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

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