Senior 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. 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