About the role
We are looking for a Data & BI Developer with 5-7 years of experience to build scalable data solutions and deliver business intelligence solutions using Microsoft Fabric and Power BI.
The role requires a strong combination of data engineering, ETL/ELT, Lakehouse development, data modeling, semantic modeling, and Power BI. Candidate should be comfortable working across the complete data lifecycle (Source data to BI Layer)
What you'll do
1. Data Engineering & Microsoft Fabric
• Develop data pipelines using Fabric Data Factory / Data Pipelines.
• Build and manage Lakehouse-based data platforms.
• Work with OneLake, Lakehouse, Data Warehouse, Notebooks, Spark, and SQL. • Implement Bronze, Silver, Gold / Curated data layers.
• Build reusable and scalable data ingestion and transformation processes.
• Work with structured and semi-structured data from multiple source systems. • Implement incremental loads, historical data processing, and data refresh strategies. • Monitor and troubleshoot data pipelines and resolve failures.
2. ETL / ELT & Data Transformation
• Develop robust ETL/ELT pipelines for data ingestion and transformation.
• Perform data cleansing, validation, standardization, and enrichment.
• Develop transformations using SQL and PySpark/Python.
• Implement appropriate error handling, logging, and monitoring.
• Optimize pipeline performance and processing time.
• Support large datasets and historical data requirements.
3. Data Modeling & Data Mart Development
• Develop fact and dimension tables using star-schema principles.
• Build analytical data marts for different business domains.
• Apply appropriate normalization and denormalization techniques.
• Create reusable and trusted datasets for BI and analytics.
• Ensure consistent business logic and KPI definitions.
• Work with stakeholders to translate business requirements into appropriate data models.
4. Power BI & BI Development
• Design and develop Power BI dashboards and reports.
• Develop optimized Power BI semantic models.
• Build appropriate relationships between fact and dimension tables.
• Develop DAX measures, calculated columns, and KPIs.
• Use Power Query for data preparation where required.
• Implement appropriate Power BI visualization and dashboard design.
• Develop drill-downs, drill-throughs, filters, tooltips, bookmarks, and interactive reporting experiences.
• Optimize Power BI reports and semantic models for performance.
• Work with stakeholders to understand reporting and analytical requirements. • Convert business requirements into meaningful dashboards and insights..
5. Data Quality & Governance
• Implement data quality checks within pipelines and data models.
• Identify and resolve data completeness, accuracy, duplication, and consistency issues. • Ensure data used in dashboards is reliable and traceable.
• Maintain appropriate documentation for data pipelines, models, KPIs, and business rules. • Follow enterprise data security and governance standards.
Qualifications
Data Engineering
• 5–7 years of relevant experience in Data Engineering / BI development. • Strong SQL skills.
• Hands-on experience with ETL/ELT.
• Experience with Microsoft Fabric or similar modern data platforms.
• Experience with Fabric Data Pipelines / Data Factory.
• Experience with Lakehouse architecture.
• Understanding of Medallion Architecture.
• Experience with SQL and PySpark/Python.
• Experience working with large datasets and historical data.
• Understanding of data quality and pipeline monitoring.
BI & Power BI
• Strong hands-on experience with Power BI.
• Strong understanding of Power BI semantic models.
• Good knowledge of DAX.
• Good knowledge of Power Query / M.
• Strong understanding of star schema and dimensional modeling.
• Experience developing fact and dimension models.
• Experience designing executive and operational dashboards.
• Understanding of Power BI performance optimization.
• Knowledge of Import, DirectQuery, and Direct Lake concepts.
• Experience implementing row-level security is a plus.
Core Skill Profile
Data Engineering: Microsoft Fabric | Data Pipelines | ETL/ELT | Lakehouse | Medallion Architecture | SQL | PySpark/Python
Data Modeling: Star Schema | Fact & Dimensions | Data Marts | Golden/Curated Layer | Semantic Models
BI: Power BI | DAX | Power Query | KPI Development | Dashboard Design | Performance Optimization
