Senior Analyst - Data & Analytics

Job Summary

The Data Analyst will support GGB UK s Chief Data Office by analysing business and operational datasets, writing SQL queries, building and validating reports, and producing insights that support data quality, governance, and business decision-making initiatives.

The role is suited for a mid-level analytics professional with strong hands-on experience in SQL, Advanced Excel, Power BI or similar BI tools, data validation, data profiling, and stakeholder-facing analysis.

The role will work closely with Data Owners, Data Stewards, Business Analysts, Data Engineers, Product Owners, and governance stakeholders to understand data structures, identify data quality issues, support root cause analysis, and help improve trust in critical data assets.

Responsibilities

• Data Analysis and SQL Querying: Extract, query, join, transform, and analyse data from relational databases, data warehouses, source system extracts, and reporting layers using SQL and other approved tools.

• Data Profiling and Validation: Perform data profiling, reconciliation, cleansing analysis, validation checks, and exception

• Dashboarding and Reporting: Develop, maintain, and validate dashboards, reports, MIS packs, KPI trackers, and ad-hoc analysis using Power BI, Advanced Excel, or equivalent reporting tools.

• Data Quality and Root Cause Analysis: Investigate data anomalies, mismatches, reporting defects, and quality exceptions by tracing source-to-target flows, reviewing business rules, and collaborating with technology and business teams.

• Data Governance Support: Support CDO-led initiatives including data definitions, Critical Data Elements, data lineage, metadata capture, data ownership, stewardship activities, issue logs, control evidence, and governance forum packs.

• Stakeholder Management: Work with business users, Data Stewards, Product Owners, Data Engineers, and reporting teams to understand requirements, clarify data definitions, validate outputs, and communicate findings clearly.

• Documentation and Knowledge Management: Maintain data dictionaries, mapping documents, business rules, profiling observations, analysis notes, SOPs, and issue-resolution documentation to ensure repeatability and auditability.

• Continuous Improvement and Automation: Identify opportunities to automate repetitive analysis, improve dashboard reliability, strengthen data controls, and create reusable reporting or validation routines using Excel, Power Query, SQL, Python, or similar tools where applicable.

  Qualifications

• Minimum Required Degree: Bachelors degree

• Preferred Degree: Bachelor s or Master s degree in Computer Science, Information Technology, Data Analytics, Statistics, Mathematics, Engineering, Business Analytics, Commerce with analytics specialisation, or a related quantitative discipline

• Certificate(s)/Special Training: Preferred certification or training in SQL, Power BI, Advanced Excel, Data Analytics, Data Quality, Data Governance, Microsoft Fabric, Azure Data Fundamentals, Snowflake, Collibra, Alation, Informatica, or equivalent data management platforms

• Experience (Career Level Guide): Mid-Level: 3 to 6 years of experience in data analysis, business intelligence, SQL-based data extraction, dashboarding, data validation, data quality analysis, reporting, or data governance support. Experience in BFSI, insurance, consulting, shared services, or global capability centre environments is preferred but not mandatory.

• Knowledge, Skills and Ability: Strong hands-on SQL skills, including joins, subqueries, aggregations, window functions, data extraction, query validation, and troubleshooting; Advanced Excel skills including pivot tables, lookups, formulas, Power Query, data cleansing, validation, reconciliation, and large dataset analysis; Experience building or supporting Power BI dashboards, reports, data models, DAX measures, KPIs, and recurring MIS or operational reporting packs; Ability to interrogate relational databases, data warehouses, source system extracts, and reporting layers to answer business questions and investigate data issues; Understanding of data quality dimensions such as completeness, accuracy, consistency, validity, timeliness, uniqueness, and integrity; Experience with data profiling, cleansing analysis, reconciliation, exception reporting, root cause analysis, and issue tracking; Working knowledge of data governance concepts including data ownership, stewardship, metadata, business glossary, lineage, Critical Data Elements, controls, and issue management; Ability to translate business requirements into analysis outputs, dashboards, reports, data checks, and clear documentation; Good communication and stakeholder-management skills, with the ability to explain data issues and insights to technical and non-technical audiences; Exposure to Python, Power Automate, Microsoft Fabric, Azure Data Services, Snowflake, Databricks, Collibra, Alation, Informatica, Tableau, or similar tools is desirable

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