Expectations / Requirements
Strong understanding of business analytics, statistical analysis, data interpretation and advanced analytical methodologies.
Ability to independently identify business problems, formulate hypotheses, analyse data and derive meaningful inferences.
Strong expertise in database management, data warehousing, data modelling and large-scale data processing.
Advanced proficiency in SQL, including complex queries, joins, window functions, query optimisation and performance tuning.
Hands-on experience with data extraction, transformation, validation and integration across multiple data sources.
Ability to design and implement scalable data management and reporting frameworks.
Experience in building automated dashboards, MIS and business intelligence solutions for senior management.
Ability to interpret complex datasets and communicate findings through clear, structured and actionable business recommendations.
Strong stakeholder management skills with the ability to work across business and technology teams.
Superpowers / Skills That Will Help You Succeed in This Role
Experience & Domain Knowledge
8–12 years of relevant experience in Business Analytics, Data Analytics, Business Intelligence or Data Management, with relevant leadership experience.
Prior experience in Fintech, Digital Payments, Banking, Financial Services or large-scale transaction-processing environments is strongly preferred.
Experience managing and mentoring teams of Business Analysts and Data Analysts.
Demonstrated experience in handling large-volume transactional datasets and developing enterprise-level analytical solutions.
Technical Skills
Advanced SQL and database technologies such as MySQL, PostgreSQL, Oracle or similar relational databases.
Hands-on experience with data warehouses and big data technologies such as Hive, Spark, BigQuery, Snowflake or Redshift.
Strong understanding of database design, data modelling, indexing, query optimisation and performance tuning.
Working knowledge of ETL/ELT tools, data pipelines and workflow orchestration frameworks.
Proficiency in Python or R for data analysis, statistical modelling and automation.
Expertise in business intelligence and visualisation tools such as Power BI, Tableau, Looker or Google Looker Studio.
Advanced Excel and PowerPoint skills.
Understanding of cloud-based data platforms and modern data architecture.
Familiarity with data governance, data quality frameworks, metadata management and data security practices.