Data & BI Developer

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.

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