Data Analyst

Job Description

• Write and maintain complex SQL queries in BigQuery and PostgreSQL to extract, transform, reconcile and analyse large volumes of financial and operational data.
  
• Perform data transformation using complex SQL logic, including multiple joins, CTEs, subqueries, window functions, aggregations, conditional logic and date-based transformations to convert raw transactional data into structured datasets for reporting and accounting purposes.
  
• Build and maintain SQL queries that transform data from multiple sources, including bank transactions, payment processors, customer transactions, internal databases and operational systems, into a consistent and reconciled view of financial activity.
  
• Own transaction-level reconciliation processes by developing SQL-based checks to match inflows and outflows across bank statements, payment processors and internal systems, and identify unmatched, duplicate, missing or incorrectly recorded transactions.
  
• Investigate data discrepancies by tracing transactions across different tables and systems, identifying the underlying data or system issue and determining whether the root cause is related to business logic, data transformation, system behaviour or data entry.
  
• Work closely with Finance to translate accounting and reporting requirements into SQL-based data logic, ensuring that reports and accounting outputs accurately reflect the underlying transactions and agreed accounting treatment.
  
• Perform controlled database-level corrections and updates where required, following appropriate validation, approval and documentation procedures, and ensure that changes are traceable and do not compromise data integrity.
  
• Build data quality checks and reconciliation controls using SQL to identify anomalies, missing records, duplicate transactions, incorrect mappings and inconsistencies between systems.
  
• Develop and maintain dashboards and recurring reports using Metabase or similar BI tools, with SQL serving as the underlying data and transformation layer.
  
• Support the automation of financial and operational reporting by developing scalable SQL-based datasets, scheduled queries and automated validation checks.
  
• Collaborate with Technology and Product teams to investigate data and system issues, validate system outputs, test changes and ensure that system-generated data is consistent with the expected business and accounting logic.
  
• Document important SQL logic, data transformations, reconciliation rules and accounting mappings to ensure that processes are maintainable and understandable by other team members.
  

Required Skills

• Advanced SQL skills are mandatory. Candidates should be comfortable independently writing complex SQL queries rather than relying primarily on pre-built datasets or BI-tool functionality.
  
• Strong hands-on experience with Google BigQuery, including querying large datasets and writing efficient and scalable SQL.
  
• Strong understanding of SQL concepts including CTEs, complex joins, subqueries, window functions, aggregations, CASE statements, date/time functions, UNIONs and data transformation techniques.
  
• Experience transforming raw transactional data into structured datasets for financial reporting, accounting, reconciliation or analytics.
  
• Strong understanding of relational databases and data structures, with practical experience working with PostgreSQL or similar databases.
  
• Experience identifying and resolving data quality issues through SQL, including duplicate, missing, inconsistent or incorrectly mapped records.
  
• Experience with BI/reporting tools such as Metabase, Power BI or Tableau, with the ability to build reports using SQL-based datasets.
  
• Familiarity with ETL/data pipeline concepts and tools such as AWS Glue is a plus.
  

Qualifications
Bachelor's degree in Data Science, Computer Science, Finance, or a related field, with 2–4 years of hands-on experience in data analytics, SQL-based data analysis, financial data, fintech, payments or a related analytical role.

This is a hands-on data analytics role. The successful candidate is expected to spend a significant portion of their time writing SQL, transforming data and building data-driven solutions rather than primarily preparing manual reports or coordinating data requests.