Senior Data Analyst

JD-Banking domain is mandatory.

1. Business & Domain Understanding

• Translating business requirements into data structures and mappings
• Working with SMEs to define business terms and KPIs
• Understanding how data is consumed (reports, dashboards, analytics, APIs) and designing models accordingly

1. Data Modeling & Mapping

• Conceptual, logical, and physical data models; Normalization & Denormalization and when to use each
• Entity-relationship (ER) modelling; Dimensional modelling;Slowly Changing Dimensions (SCD types)
• Understand existing data model and alignment; work experience in ERwin,Maintaining models as living artefacts (versioning, change tracking)

o Source-to-target mapping (STM) / mapping specifications; Maintain Data Mapping & data dictionary document aligning standards.

o Understanding of source systems: APIs, databases, flat files, messages

o Mapping business concepts to data elements and attributes;Handling data transformations: cleansing, standardization, enrichment

• Understanding how models and mappings are implemented in ETL;How mapping specs are handover docs for ETL developers / engineers

1. SQL & Querying

o Strong SQL for exploring data and validating models;Joins, aggregations, window functions

o Strong data profiling to refine models and mappings

1. Testing & Data Validation

o Documenting validation rules, thresholds, and exception criteria;Translating business and technical requirements into test cases

o Defining test scenarios, test data, expected results; Executing manual test cases, validating results, logging defects

o Using or scripting automation (e.g., SQL scripts, Python, or test tools) for repeatable checks

o Perform Data validation, Support UAT & UVT

o Test cases tracking and update in ADO; Incident Handling

1. Data Quality, Standards & Governance

o Data quality dimensions: accuracy, completeness, consistency, timeliness, uniqueness

o Designing models that support data quality checks and constraints

o Metadata: business glossary, data catalog, data lineage

o Naming conventions, standards for keys, data types, and codes

1. Documentation & Communication

o Clear mapping &model documents: field-level mappings, transformation rules, validation rules

o Communicating models and mappings to business stakeholders and technical teams

o Participating in design and review workshops