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Power BI - Data Engineer Position: Power BI - Data Engineer Job Description: Power BI / Azure Data Engineer Job Description Position : Power BI and Azure Data Engineer Job Summary We are looking for a skilled and detail-oriented Power BI / Data Analytics Engineer with 46 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, and Python, 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 Azure Data Factory, Databricks (PySpark/SQL), and modern data integration frameworks. Develop Python scripts for automation, data processing, validation, and workflow optimization. Integrate data from multiple enterprise systems including SQL Server, Oracle, SAP, ERP, APIs, Azure platforms, and cloud data warehouses. Work with modern cloud platforms including Microsoft Azure, Databricks, Snowflake, Microsoft Fabric, Synapse Analytics, and SQL Server. 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 Medallion Architecture (BronzeSilverGold) and Lakehouse 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 Azure Data Factory and Databricks (PySpark/SQL). Strong understanding of Medallion Architecture (Bronze, Silver, Gold). Working knowledge of Delta Lake, schema evolution, MERGE/Upsert, and ACID transactions. Experience with orchestration, monitoring, and pipeline optimization. Data Warehousing & Cloud Platforms Experience with Microsoft Azure, Microsoft Fabric, Databricks, Snowflake, Azure Synapse Analytics, SQL Server, or equivalent cloud 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, or cloud databases. Knowledge of semantic modeling and enterprise reporting architecture. Engineering Best Practices Experience using Git/version control. Experience implementing CI/CD pipelines using Azure DevOps or GitHub. Familiarity with Agile/Scrum methodologies. Strong documentation, troubleshooting, and code review practices. Data Governance & Security Experience implementing metadata management, lineage, and governance using Microsoft Purview or Microsoft Fabric governance capabilities. Knowledge of RBAC, workspace security, data privacy, PII handling, and encryption best practices. Secondary Skills (Good to Have) Exposure work with Microsoft Fabric (Lakehouse, Warehouse, Data Factory, OneLake .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.