/or Scala. * Expertise in ETL/ELT processes, data warehousing, and data mesh architectures. * Familiarity with AI/ML concepts and their application in data analytics. * Experience with metadatamanagement, data lineage tracking, and data cataloguing. * Knowledge of serverless data processing, event-driven architectures, and modern data stacks. In accordance with the Employment Agencies and Employment Businesses More ❯
data dictionary management. Proficiency in SQL, Python, R, or other data science tools and frameworks. Experience leading data or analytics teams and mentoring junior staff. Strong communication and stakeholder management skills. Working experience of below skill sets- Data Analytics Data Modelling Data Science Building of data models Working knowledge of implementation of Strategic project. Experience in Data Visualization and … on strategic, cross-functional data initiatives with C-level stakeholders. Familiarity with cloud data platforms (e.g., Azure, AWS, GCP, Snowflake). Knowledge of data governance standards, regulatory compliance, and metadata management. Experience with BI and visualization tools such as Power BI, Tableau, or Looker. Certification in data science, analytics, or cloud technologies (e.g., Microsoft, AWS, Google). Why join More ❯
ROLE As a Data Modeller in the Financial Services domain, you will be responsible for designing, developing, and maintaining data models that support critical business functions such as risk management, regulatory reporting, investment analytics, and operational efficiency. You will work closely with stakeholders across business and technology to ensure data structures are optimized for performance, compliance, and usability. YOUR … systems. Collaborate with business stakeholders to gather and understand data requirements. Translate business needs into scalable and high-performance data models. Apply industry best practices in data modeling and metadata management. Work closely with data engineers and analysts to ensure seamless data integration. Create and maintain data dictionaries and metadata repositories . Ensure data quality , consistency, and governance More ❯
