Keyrus

• Design, develop, and maintain scalable data pipelines using Databricks, PySpark, Python and SQL. • Build and optimise batch and near real-time data processing solutions on the Microsoft Azure ecosystem. • Develop and maintain Delta Lake-based data architectures. • Develop robust and scalable data products and modern data platform components supporting strategic business initiatives. • Contribute to CI/CD implementation and automation for data solutions. • Apply engineering best practices around source control, testing, deployment, and monitoring. • Support Infrastructure-as-Code and environment standardisation initiatives. • Ensure high standards of data quality, observability, monitoring, security, and operational reliability. • Collaborate with Product Managers, Architects, Data Engineers, and business stakeholders to deliver high-quality outcomes. • Participate in technical design discussions and contribute to solution architecture decisions. • Support platform governance, cost optimisation, technical documentation, and knowledge sharing initiatives.

• Define and industrialise Data Quality frameworks , including KPIs/KQIs, control catalogues, and remediation workflows • Lead Data Quality governance processes , including detection forums, incident management, tracking, and resolution follow-up • Design, deploy, and optimise Agentic AI solutions to enhance business processes (e.g., automated documentation, control generation, incident pre-triage, reporting) • Contribute to change management deliverables and communication materials • Drive change management and user adoption by engaging Data Owners, Data Stewards, and IT stakeholders (DSO, Application Owners), developing capabilities on new processes and tools, delivering training , providing hands-on support , and overcoming resistance to change.

• Design, develop, and maintain scalable data pipelines and integration solutions within the Azure ecosystem • Build and support enterprise data platforms that consolidate information from multiple source systems • Develop ETL/ELT processes to ingest, transform, validate, and distribute business-critical data • Contribute to data modelling, data quality, and governance initiatives • Support Master Data Management (MDM) processes and ensure consistency across systems • Work with structured and semi-structured data from ERP, business applications, APIs, databases, and external sources • Collaborate with business and technical stakeholders to translate requirements into scalable data solutions • Participate in deployment, testing, monitoring, and continuous improvement activities • Contribute to CI/CD pipelines, automation, and DevOps best practices • Actively participate in Agile ceremonies and team collaboration

• Develop and scale enterprise web applications using Angular • Integrate frontend applications with Python/FastAPI backends • Implement GPT/LLM-based modules to support evaluation, automation, and workflow optimisation • Design, build, and consume REST APIs within a microservices architecture • Implement secure authentication and authorisation mechanisms • Collaborate closely with Data Science and platform teams to integrate AI capabilities • Participate in technical architecture discussions and contribute to system design decisions • Ensure scalability, maintainability, and performance of applications • Contribute to Agile ceremonies and delivery planning • Support deployment, integration, and release activities across environments

• Perform the upgrade of a SAP BusinessObjects BI Platform 4.3 sandbox environment to a higher Support Pack, including all necessary pre‑checks, execution, and post‑upgrade validation • Ensure continuity of service through proper testing, risk mitigation, and controlled delivery • Produce clear installation, configuration, and upgrade documentation • Create end‑user training materials covering both standard and newly introduced functionalities • Configure and validate SSO and Azure Active Directory integrations • Configure and validate Microsoft OneDrive integration with SAP BO • Work with and validate features such as Workflow Assistant • Execute a clean handover to internal SAP BO Administrators, ensuring autonomy after project completion • Communicate effectively with technical and non‑technical stakeholders throughout the assignment

• Develop and scale enterprise web applications using Angular • Integrate frontend applications with Python/FastAPI backends • Implement GPT/LLM-based modules to support evaluation, automation, and workflow optimisation • Design, build, and consume REST APIs within a microservices architecture • Implement secure authentication and authorisation mechanisms • Collaborate closely with Data Science and platform teams to integrate AI capabilities • Participate in technical architecture discussions and contribute to system design decisions • Ensure scalability, maintainability, and performance of applications • Contribute to Agile ceremonies and delivery planning • Support deployment, integration, and release activities across environments

• Design, develop, and maintain scalable data pipelines and integration solutions within the Azure ecosystem • Build and support enterprise data platforms that consolidate information from multiple source systems • Develop ETL/ELT processes to ingest, transform, validate, and distribute business-critical data • Contribute to data modelling, data quality, and governance initiatives • Support Master Data Management (MDM) processes and ensure consistency across systems • Work with structured and semi-structured data from ERP, business applications, APIs, databases, and external sources • Collaborate with business and technical stakeholders to translate requirements into scalable data solutions • Participate in deployment, testing, monitoring, and continuous improvement activities • Contribute to CI/CD pipelines, automation, and DevOps best practices • Actively participate in Agile ceremonies and team collaboration

• Perform the upgrade of a SAP BusinessObjects BI Platform 4.3 sandbox environment to a higher Support Pack, including all necessary pre‑checks, execution, and post‑upgrade validation • Ensure continuity of service through proper testing, risk mitigation, and controlled delivery • Produce clear installation, configuration, and upgrade documentation • Create end‑user training materials covering both standard and newly introduced functionalities • Configure and validate SSO and Azure Active Directory integrations • Configure and validate Microsoft OneDrive integration with SAP BO • Work with and validate features such as Workflow Assistant • Execute a clean handover to internal SAP BO Administrators, ensuring autonomy after project completion • Communicate effectively with technical and non‑technical stakeholders throughout the assignment

• Design, implement, and maintain enterprise data warehouse solutions following Data Vault 2.0 methodology • Develop and optimise Hubs, Links, Satellites, PIT, and Bridge tables • Lead conceptual, logical, and physical data modelling activities across multiple initiatives • Define and promote data architecture standards, modelling guidelines, naming conventions, and documentation practices • Ensure scalability, performance, reliability, and maintainability of data warehouse architectures • Provide technical leadership and architectural guidance to Data Engineers and development teams • Drive the standardisation and automation of ELT processes, metadata management, and deployment practices • Collaborate closely with Business Analysts, Product Owners, Data Governance teams, and other stakeholders to translate business requirements into robust data solutions • Support reporting and analytics teams by delivering optimised and business-ready data structures

• Design, build, and maintain data pipelines and integrations across multiple systems • Translate business and functional requirements into technical data solutions • Work with structured and unstructured data to support analytics and GenAI use cases • Integrate data pipelines with APIs, backend systems, and AI/LLM modules • Collaborate with business stakeholders, Data Scientists, and engineers to ensure data usability and alignment • Support data quality, governance, and validation processes • Contribute to data modelling, transformation logic, and pipeline optimisation • Support Agile delivery processes, backlog refinement, and sprint execution • Ensure alignment between technical delivery and business objectives • Participate in architecture discussions and solution design decisions