Job Title : Senior Data Architect - Azure Databricks / Snowflake / Power BI / Microsoft Fabric

Experience : 6 - 12 Years

Positions : 5

Work Location : Bangalore - ITPL, Whitefield

Work Mode : Hybrid (3 days per week from office)

Notice Period : Immediate to 15 Days Only

Company Overview :

GyanSys is a global systems integrator specializing in digital transformation through SAP, Salesforce, Microsoft, Databricks, Snowflake, application modernization, and AI-led solutions. The organization serves enterprise customers across industries, helping them modernize business processes and build scalable technology solutions.

Job Summary :

GyanSys is looking for experienced Data Architects, Lead Data Engineers, and Principal Data Professionals with strong expertise in Azure Databricks, Snowflake, Power BI, Microsoft Fabric, and SQL. The ideal candidate should have a strong background in data engineering, business intelligence, cloud data architecture, and enterprise analytics solutions.

The candidate will be responsible for designing and optimizing scalable data architectures, building robust ETL/ELT pipelines, developing enterprise reporting solutions, and delivering end-to-end data platforms. This role requires strong technical expertise, architectural thinking, and the ability to collaborate with cross-functional teams to deliver high-performance data solutions.

Key Responsibilities :

- Design, develop, and optimize scalable data pipelines using Azure Databricks, Snowflake, Microsoft Fabric, and other cloud-based technologies.

- Architect and implement enterprise data solutions supporting large-scale analytics and business intelligence requirements.

- Develop and maintain Power BI dashboards and reports using advanced DAX, Power Query, and data modelling techniques.

- Design and implement robust ETL/ELT workflows using SQL and cloud-based data integration tools.

- Leverage Azure Databricks for large-scale data processing, transformation, and optimization in distributed computing environments.

- Design and optimize data warehouse architectures to support enterprise reporting and analytical workloads.

- Work with Microsoft Fabric capabilities to build integrated data engineering and analytics solutions.

- Ensure data accuracy, consistency, security, and performance across data pipelines and reporting platforms.

- Optimize SQL queries, data models, warehouse performance, and data processing workflows.

- Collaborate with business stakeholders, data engineers, BI developers, and cloud architects to deliver end-to-end data solutions.

- Establish best practices for data governance, data quality, automation, documentation, and platform management.

- Identify opportunities to improve data architecture, scalability, reliability, and operational efficiency.

Mandatory Skills & Qualifications :

- 6+ years of experience in Data Engineering, Data Architecture, or Business Intelligence development.

- Strong hands-on experience with Azure Databricks and distributed data processing.

- Experience designing and developing scalable ETL/ELT pipelines.

- Strong expertise in Snowflake and cloud data warehouse architecture.

- Hands-on experience with Power BI, including advanced DAX, Power Query, and data modelling.

- Knowledge of Microsoft Fabric and its data engineering and analytics capabilities.

- Strong SQL skills, including query optimization and performance tuning.

- Experience with data integration, transformation, and large-scale analytics solutions.

- Understanding of data governance, data quality, security, and automation practices.

- Ability to design scalable data solutions and work across multiple cloud platforms.

- Strong communication, analytical, and problem-solving skills.

Good to Have :

- Experience with enterprise-scale cloud data architecture and multi-cloud environments.

- Knowledge of Azure Data Factory, Azure Data Lake Storage, and related Azure services.

- Exposure to OneLake, Lakehouse architecture, and Microsoft Fabric workloads.

- Experience with CI/CD, automation, and data pipeline orchestration.

- Experience leading technical teams or mentoring data engineering professionals.