At IAG GBS, high-quality, reliable data is essential for efficient Finance Operations, accurate reporting and effective process performance. The Data Analyst (SQL & Data Quality) plays a key role in ensuring data integrity across multiple systems, processes and Operating Companies.
In this role, you will apply strong SQL capabilities and analytical thinking to evaluate data quality, build and optimise validation logic, investigate anomalies, and support continuous improvement. You will work closely with Process Analytics, Finance Operations and cross-functional stakeholders to strengthen the visibility, accuracy and governance of data across the organisation.
This role is ideal for someone who thrives on solving data inconsistencies, designing queries that uncover hidden issues, and collaborating with finance and technical teams to improve end-to-end data quality.
responsibilities :
Develop, refine and optimise complex SQL queries, joins and validation rules across large datasets.
Perform data profiling, identify anomalies, inconsistencies and missing key fields.
Conduct root cause analysis and propose corrective and preventive actions.
Ensure efficient processing of queries through performance tuning and query optimisation.
Maintain and enhance rule-based validation logic for Finance Operations datasets.
Support integration of new data sources, tables and fields into data quality checks.
Document logic, validation standards and exception handling processes.
Ensure consistency, traceability and transparency of data quality outputs.
Collaborate with Finance Operations teams to understand data challenges and provide analytical insights.
Provide reports and insights that highlight trends, root causes and systemic data concerns.
Support operational governance forums with data-driven findings.
Work closely with Process Analytics, IT/Data teams, and other OpCos to align on data logic and requirements.
Participate in workshops and working groups related to data quality improvement.
Translate business requirements into SQL specifications and analytical outputs.
Communicate findings in a structured way to both technical and non-technical stakeholders.
Identify opportunities to automate checks, streamline data pipelines and strengthen validation frameworks.
Propose enhancements to datasets, data structures and field usage that improve data reliability.
Contribute to the development of data quality best practices, playbooks and documentation.
Support potential future use of dashboarding tools (e.g., Tableau, Power BI) to visualise data quality trends.
requirements-expected :
Degree in finance, economics, business information systems, data analytics or a related field.
Degree in computer science, information systems, data analytics, finance or related field.
Advanced proficiency in SQL, including complex joins, subqueries, window functions and performance optimisation.
Experience with data quality, data validation, data governance or data cleansing.
Understanding of Finance Operations processes preferred.
Experience with large datasets and relational database structures.
Ability to translate business requirements into robust SQL logic.
Experience with BI tools (Tableau, Power BI) is an advantage.
Strong analytical thinking, attention to detail and structured problem-solving.
Comfort working in multinational and cross-functional environments.
Excellent communication skills, able to simplify complex data topics.
Curiosity, proactivity and a continuous-improvement mindset.
Willingness to travel (up to 20%).
offered :
The chance to enjoy a challenging career in an exciting, fast-moving environment in a dynamic industry.
The opportunity to work in a multi-cultural environment with great offices in many locations. We aim to provide all our people with a work/life balance, as well as the many benefits offered by a global organisation, including health insurance, pension and performance bonuses.
We are an equal opportunities employer and all qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.
