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To implement data quality process and procedures, ensuring that data is reliable and trustworthy, then extract actionable insights from it to help the organisation improve its operation, and optimise resources.
Job Responsibility:
Investigation and analysis of data issues related to quality, lineage, controls, and authoritative source identification
Execution of data cleansing and transformation tasks to prepare data for analysis
Designing and building data pipelines to automate data movement and processing
Development and application of advanced analytical techniques, including machine learning and AI, to solve complex business problems
Documentation of data quality findings and recommendations for improvement
Requirements:
Hands on experience in modern data analytics platforms and reporting data warehouses
Deep Understanding of Data warehousing principles with hands on knowledge on scalable data ingestion techniques through secure pipelines
Ability to perform business and data analysis alongside working with technology colleagues, developers and business stakeholders
Working experience on Agile methodologies like Scrum, Kanban or any other Agile framework
Working experience of using Python for Data Analysis & Profiling
Ability to translate business requirements into technical stories
Solid written and verbal communication skills
Ability to be proactive, a team player and having a ‘can-do’ attitude
Nice to have:
Knowledge in Retail, Investment Bank or Correspondent Banking Anti-Money Laundering (AML) Transaction Monitoring
Knowledge of data modelling techniques and exposure to any modelling tool preferred
Exposure to data controls techniques would be an added advantage
Knowledge and understanding of Data Analysis and Visualization tools like SQL/Tableau/Power BI, etc
Certification in AWS, Databricks Lakehouse, DBT Fundamentals would be an added advantage