Data Analyst-TMF Group

The Data Analyst works closely with Data Architects, Data Engineers, Business Analysts, and business stakeholders to ensure data requirements are translated into reliable and governed datasets for reporting, analytics, and operational processes.

• Analyze source and target system data structures.
• Define data mappings between systems.
• Document transformation logic and business rules.
• Identify data gaps, inconsistencies, and dependencies.
• Support data migration and conversion activities.

Typical Deliverables

• Source-to-Target Mapping (STTM) documents
• Data dictionaries
• Transformation specifications
• Business rule documentation

2. Azure & Microsoft Fabric Data Support

• Support data ingestion, transformation, and validation processes.
• Work with Azure data services and Microsoft Fabric environments.
• Monitor data pipelines and troubleshoot data issues.
• Validate outputs generated by ETL/ELT processes.
• Assist data engineering teams during data processing activities.

Technologies Involved

• Microsoft Fabric
• Azure Data Factory (ADF)
• Azure Data Lake
• Azure Synapse Analytics
• Power BI
• SQL-based data warehouses

3. Data Validation & Reconciliation

• Perform data quality checks.
• Compare source and target datasets.
• Validate completeness and accuracy of migrated data.
• Execute reconciliation testing.
• Investigate and resolve data anomalies.

Typical Activities

• Record count validation
• Data completeness checks
• Duplicate identification
• Exception reporting
• Reconciliation reporting

4. Data Modelling Support

• Assist in creating logical and physical data models.
• Validate relationships between entities and data structures.
• Support dimensional modelling initiatives.
• Ensure alignment between business requirements and data models.

Data Modelling Concepts

• Entity Relationship Diagrams (ERD)
• Star Schema
• Snowflake Schema
• Facts and Dimensions
• Business Data Models

5. Master Data Management (MDM)

• Support master data cleansing activities.
• Assist in defining data standards.
• Identify duplicate and inconsistent records.
• Help establish golden records and reference data standards.

Common Master Data Domains

• Customer Data
• Employee Data
• Vendor Data
• Product Data
• Financial Data

6. Data Governance Support

• Maintain metadata documentation.
• Support data lineage tracking.
• Assist with governance and compliance initiatives.
• Contribute to data catalog management.
• Help improve data stewardship processes.

Areas of Governance

• Metadata Management
• Data Lineage
• Data Ownership
• Data Stewardship
• Data Quality Management

7. Testing Support

• Execute system and data testing activities.
• Prepare test scenarios and test cases.
• Support User Acceptance Testing (UAT).
• Validate transformed data against business requirements.
• Report defects and track resolutions.

Technical Skills

Data Analysis

• Data profiling and ass