Data Analyst (Power BI/ Tableau)

About The Role

You will play a critical role in enabling safe, evidence-based decision making, and You will ensure that complex transformation decisions are underpinned by trusted data, transparent logic, and clearly articulated insights.

Data Analyst

• Strong Data Quality experience
• Data migration experience
• Experience with Teradata is good to have, as the source data resides in Teradata

In this role, you will be expected to challenge constructively, surface risk early, and help leaders navigate ambiguity by turning complex data into simple, trusted narratives.

Responsibilities

• Validate data flows across complex, multi‑system business and technology landscapes
• Complete source‑to‑target mapping, transformation logic validation and reconciliation across legacy and target‑state platforms
• Conduct data quality profiling and issue analysis, translating defects into actionable remediation insights
• Define and document data sourcing, controls and assumptions to support regulatory, audit, and governance expectations

Required Skills

• Good experience delivering data analytics within large‑scale transformation, regulatory, or technology uplift programs.
• Hands‑on capability across SQL, Python, Excel and data visualisation (Power BI / Tableau)
• Proven experience in source‑to‑target mapping, data profiling, reconciliation and analysis of end‑to‑end business processes and data flows
• Experience with Teradata and preferred knowledge
• Deep understanding of data structures, state models, data lineage and knowledge/familiarity with statistical methods of data analysis.
• Strong knowledge of data quality dimensions (completeness, validity, accuracy, consistency, uniqueness, integrity, reliability, timeliness) and how to embed them within analytical pipelines
• In terms of experience, 5 years within Data Analyst /Business Data Analyst or related roles.
• Required educational requirements, aspirant should have bachelor’s or master’s degree in computer science, engineering, finance or statistics/mathematics, information systems, data science, certifications (optional but valuable), etc.