Data Analyst

Strong hands-on experience with Databricks for data analysis, exploration, validation, and troubleshooting. Advanced SQL querying and scripting skills, with the ability to work with complex and large-scale datasets. Strong experience in data analysis, data profiling, reconciliation, and Data Quality (DQ) validation. Ability to explore large datasets and translate analysis into clear findings, recommendations, and actionable insights. Experience working with large volumes of data and understanding of performance optimisation techniques. Ability to identify inefficient queries or data-processing patterns and work with Data Engineers to improve performance. Hands-on knowledge of Python and PySpark for data analysis and large-scale data processing. Ability to bring together data from multiple online and offline data sources, perform QC/reconciliation, and derive meaningful insights. Strong understanding of data relationships, transformations, business rules, and data lineage. Ability to understand business requirements and translate them into data requirements, analysis, validation rules, and acceptance criteria. Experience with Git-based version control and working within standard development and review processes. Ability to document data definitions, business rules, mappings, analysis findings, and validation outcomes. Ability to collaborate with Data Engineers, Data Architects, BI teams, QA teams, Product Owners, and business stakeholders to brainstorm and implement solutions. Good communication skills with the ability to present analysis and explain data findings clearly to both technical and non-technical stakeholders. Experience working in Agile/Scrum delivery environments.