This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
Design, develop, and optimize complex SQL queries, stored procedures, and data pipelines to process and analyze large-scale structured datasets from SQL Server and Snowflake environments
Create a delegate business analysis and test the data from end-to-end validation
Document all the test artefacts including test cases, test planes, Requirement analysis docs in JIRA
Validated all the Asset data validations and Regression on BUAT/UAT, JSIT, and Parallel PROD APIs
Engineer and deploy data validation and quality assurance frameworks using Python, SQL, and VBA to enforce data integrity, consistency, and referential accuracy
Test integration testing for UP stream and low stream services - API and DB, UI
Validate Core data, Custom data requirements on feed load, smoke test, daily load checks, regression activities, Indices and interfaces validations, PMAR data, MSCI data, and Benchmark data
Perform advanced data analysis, statistical evaluation, and reconciliation of multi-source datasets using Python (Pandas, NumPy) and SQL
Apply data modeling techniques, normalization principles, and schema design to build scalable and efficient data structures
Conduct root cause analysis (RCA) of data anomalies by performing data lineage tracing and system-level diagnostics
Support data migration, system integration, and data conversion projects through data profiling, validation, and User Acceptance Testing (UAT)
Integrate and validate external financial datasets (e.g., Bloomberg) with internal enterprise systems using automated validation logic
Develop and implement Python-based data processing frameworks and ETL pipelines for data extraction, transformation, cleansing, and integration across heterogeneous systems
Collaborate with cross-functional stakeholders to translate business requirements into technical data solutions and system specifications
Utilize enterprise tools such as JIRA and ServiceNow for defect tracking, incident management, and workflow coordination in Agile environments
Leverage AI-assisted development tools (e.g., Microsoft Copilot) to enhance productivity in coding, debugging, and technical documentation
Ensure adherence to data governance frameworks, regulatory compliance standards, and audit requirements in all data processing activities
Requirements
Bachelor's degree in Business Analytics, Information Systems, Computer Science, Statistics, Mathematics, Finance, Economics, or a closely related field
Related experience in Business Intelligence, Data Analysis, Reporting, and Dashboard Development
Strong experience with BI tools such as Power BI, Tableau, Qlik Sense, Looker, or similar data visualization platforms
Proficiency in SQL, database querying, data modeling, and working with relational databases such as SQL Server, Oracle, MySQL, or PostgreSQL
Experience gathering business requirements, analyzing data, and translating business needs into actionable insights and reports
Strong understanding of data warehousing concepts, ETL processes, data integration, and data governance practices
Experience working with large datasets and performing data validation, cleansing, and quality assurance activities
Proficiency in Microsoft Excel, including advanced formulas, pivot tables, Power Query, and data analysis techniques
Strong analytical, problem-solving, communication, presentation, organizational, and stakeholder management skills
Ability to create clear reports, dashboards, and visualizations to support executive and operational decision-making
Working knowledge of Advanced SQL (SQL Server, Snowflake),Python (Pandas, NumPy), Data Modeling, ETL Development, Data Validation Frameworks, Statistical Analysis, Excel (VBA, Macros), MS Access, Bloomberg Data Integration, JIRA, ServiceNow, Microsoft Copilot, Agile/Scrum methodologies
Nice to have
Experience with statistical analysis, forecasting, trend analysis, and KPI development
Knowledge of programming or scripting languages such as Python, R, or SAS for data analysis and automation
Experience working in Agile/Scrum environments and using project management or collaboration tools
Experience with cloud-based analytics platforms such as AWS, Azure, or Google Cloud Platform (GCP)