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Data Engineer - Power BI & Analytics
Location: Hyderabad/Hybrid
Employment Type: Full-Time
Experience: 10+ years
Working Hours: 2:00 PM-11:00 PM IST
Role Overview
We are looking for a hands-on Data Engineer with strong Power BI, data modeling, SQL, and analytics experience to work as a dedicated member of a U.S.-based enterprise client's data and analytics team. The role will work closely with business, data, and IT stakeholders to support data modeling, reporting, analytics, and ongoing data needs. This is not purely a backend data engineering role - the ideal candidate should be comfortable working across the data lifecycle, from understanding source data and designing models to building Power BI reports and supporting ad-hoc analytical requests. The individual will operate as an extension of the client's internal team and should be comfortable working independently, interacting directly with stakeholders, and taking ownership of assigned deliverables.
Key Responsibilities
Design, develop, and maintain scalable data models for reporting and analytics.
Build and enhance Power BI dashboards, reports, semantic models, and datasets.
Work with business stakeholders to understand reporting requirements, KPIs, and analytical needs.
Develop and optimize SQL queries, views, transformations, and data pipelines.
Support data integration and transformation across multiple enterprise data sources.
Perform data analysis, reconciliation, validation, and troubleshooting.
Support ad-hoc reporting and analytical requests from business and technology teams.
Develop and maintain dimensional and analytical data models using appropriate modeling techniques.
Optimize Power BI models and reports for performance, usability, and maintainability.
Implement and support appropriate data access and security models, including row-level security where required.
Investigate data-quality issues and work with source-system and data teams to resolve them.
Document data models, report logic, transformation rules, and key dependencies.
Participate in regular discussions with U.S.-based stakeholders and provide clear status updates on deliverables, risks, and dependencies.
Support ongoing production reporting and analytics needs as part of a dedicated client delivery model.
Required Skills
10+ years of experience in data engineering, business intelligence, analytics engineering, or a closely related data role.
Strong hands-on experience with Microsoft Power BI, including Power BI Desktop and Service, DAX, Power Query, semantic/data models, dashboard and report development, and performance optimization.
Advanced SQL skills and experience working with relational databases.
Strong understanding of dimensional modeling, star schemas, fact/dimension design, and analytical data structures.
Experience developing ETL/ELT pipelines and transforming data from multiple sources.
Experience working with Microsoft Azure data technologies.
Strong data-analysis and troubleshooting capabilities.
Ability to translate business requirements into reliable analytical solutions.
Strong written and verbal communication skills.
Ability to work 2:00 PM-11:00 PM IST and collaborate directly with U.S.-based stakeholders and offshore teams.
Preferred Skills
Experience with Microsoft Fabric and Fabric data workloads.
Experience with Azure Data Factory, Azure SQL, Data Lake, Synapse, or similar services.
Experience supporting enterprise reporting environments with multiple data sources.
Understanding of data governance, lineage, security, and role-based access concepts.
Experience with Git, Azure DevOps, or similar development and release practices.
Exposure to ERP, CRM, operational, financial, or other enterprise data platforms.
What We Are Looking For
We are looking for someone who combines strong engineering fundamentals with a practical analytics mindset. The successful candidate should be comfortable moving between data pipelines, SQL, data modeling, Power BI, and business-facing analytics rather than operating within a narrowly defined technical area. This is a hands-on role requiring ownership, responsiveness, and the ability to become a trusted extension of the client's internal data team.
Work arrangement
Hybrid
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