Position:

Data Engineer with Power BI - Senior engineer (Level 1)

:

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.
- Solid 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

📌 Data Engineer with Power BI - Senior engineer (Level 1) (Pune)
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📍 Pune