About the Role

We are looking for an experienced Senior Data Analyst with 5+ years of experience in data-centric technology implementations, data analysis, business process analysis and enterprise data integration.

The ideal candidate will combine robust SQL, API, data modelling and data analysis capabilities with a good understanding of Microsoft Azure, Microsoft Fabric, Oracle Fusion and enterprise data platforms.

The role will work closely with business stakeholders, product owners, engineers, compliance teams and vendors to understand data requirements, analyse complex data flows, define data mappings and translate business requirements into clear, actionable requirements for technology teams.

Experience in Banking, Financial Services will be highly advantageous.

Key Responsibilities

1. API Analysis & Data Mapping

- Analyse and document public-facing and internal APIs used across business platforms.
- Understand API endpoints, request/response structures, JSON payloads and underlying data models.
- Perform detailed mapping between API payloads and enterprise/client data models.
- Identify data gaps, inconsistencies, transformation rules and dependencies.
- Validate API responses and data using tools such as Postman or Bruno.
- Translate API and data-flow analysis into clear functional and technical requirements for engineering teams.
- Support engineers with clarification of data mappings, business rules and transformation requirements.

2. Data Analysis & Data Quality

- Analyse large and complex datasets to identify trends, anomalies, inconsistencies and data-quality issues.
- Use SQL to investigate source and target data, perform reconciliation and validate data transformations.
- Define and document data-quality rules covering completeness, accuracy, consistency, timeliness and validity.
- Investigate data breaks and work with technical teams to identify root causes and remediation requirements.
- Define reconciliation requirements between source systems, APIs, data products and downstream applications.
- Support data lineage and auditability requirements across business-critical datasets.

3. Data Sourcing & Integration Analysis

- Define requirements for migration from CSV and other flat-file sources to automated data products.
- Analyse source systems and document data ownership, data definitions, update frequency and dependencies.
- Understand data ingestion, transformation and consumption flows across enterprise data platforms.
- Work with data engineers to define requirements for data pipelines and data products without owning the engineering implementation.
- Analyse and document data flows across Azure, Microsoft Fabric and enterprise application platforms.




- Support integration requirements involving Oracle Fusion and other enterprise business systems.

4. Microsoft Fabric & Azure Data Analysis

- Work with business and technology teams to understand data products built using Microsoft Fabric.
- Analyse data across Fabric Lakehouse, Warehouse, pipelines and semantic models.
- Understand the role of Azure Data Factory, Databricks, ADLS Gen2 and Azure Synapse within enterprise data ecosystems.
- Analyse data movement and transformation processes across Azure-based platforms.
- Support requirements definition for data products, reporting datasets and analytical solutions.
- Understand data governance, metadata, lineage and catalogue concepts within modern Azure data platforms.

5. Oracle Fusion Data Analysis

- Analyse business and data flows involving Oracle Fusion applications.
- Understand Oracle Fusion data structures, entities and relationships relevant to business processes.
- Perform source-to-target data mapping between Oracle Fusion and downstream data platforms.
- Analyse data extracted from Oracle Fusion for reporting, analytics, reconciliation and integration purposes.
- Work with functional and technical teams to identify data gaps, transformation requirements and integration dependencies.

6. Business Process Analysis

- Translate business processes into data, system and workflow requirements.
- Document system configuration requirements, including alert management rules, detection thresholds, workflow steps and user permissions.
- Identify opportunities for process improvement through better data availability, quality and automation.
- Provide input into operational processes and user experience to ensure alignment with business requirements.

7. SQL & Data Investigation

- Write and execute complex SQL queries to analyse and validate data.
- Perform joins, aggregations, filtering, reconciliation and data-quality analysis across relational databases.
- Investigate source-to-target data discrepancies and identify root causes.
- Use tools such as SQL Server Management Studio (SSMS) for data investigation and validation.
- Interpret relational data models and understand relationships between business entities.

8. Testing, Validation & Delivery Support

- Define test scenarios and test cases for data, APIs, integrations and business processes.




- Validate API responses and data transformations against business requirements.
- Perform data validation and reconciliation during testing and implementation.
- Support SIT, UAT and production validation activities.
- Collaborate with engineers, product owners, compliance teams, business stakeholders and vendors.
- Track defects, clarify requirements and support timely resolution of data-related issues.

Required Skills & Experience

- 5+ years of experience as a Senior Data Analyst, Data Analyst, Business/Data Analyst or similar data-centric role.
- Strong experience in SQL and relational database analysis.
- Hands-on experience with SQL Server / SSMS or similar database technologies.
- Strong understanding of data models, data mapping and data integration concepts.
- Strong understanding of REST APIs, JSON, API endpoints and payload structures.
- Practical experience using Postman, Bruno or similar API testing tools.
- Strong experience in data-quality analysis, reconciliation and source-to-target validation.
- Good understanding of Microsoft Fabric, including Lakehouse, Warehouse, Data Pipelines and Semantic Models.
- Good understanding of Azure data concepts, including:
- Azure Data Factory
- Azure Databricks
- ADLS Gen2
- Azure Synapse
- Azure Storage
- API Management
- Azure DevOps
- Strong understanding of Oracle Fusion and its data/integration ecosystem.
- Understanding of ETL/ELT processes, data pipelines and enterprise data platforms.
- Understanding of data warehousing and data modelling concepts, including Kimball and Data Vault principles.
- Strong understanding of data governance concepts including data lineage, metadata, auditability and data quality.
- Ability to translate technical data flows and system behaviour into clear business and functional requirements.
- Strong business process analysis and documentation skills.
- Excellent stakeholder management and communication skills.
- Ability to work effectively with business users, technology teams, architects, engineers, compliance teams and external vendors.
- Comfortable working in an Agile delivery environment.

Desirable Skills

- Experience with Microsoft Purview or similar data governance/cataloguing platforms.
- Exposure to Databricks and modern cloud data platforms.
- Understanding of Azure DevOps and Agile delivery practices.
- Experience working with enterprise ERP data, particularly Oracle Fusion.
- Microsoft Azure / Fabric certifications such as DP-600, DP-700, DP-203 or AZ-900.
- Experience working on enterprise-scale data transformation or cloud-modernisation initiatives.

Domain: Banking / Financial Services / Data & Analytics

📌 Senior Data Analyst (Maharashtra)
🏢 Matisaar Technologies
📍 Maharashtra