Keyrus

• 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

• Design, develop, and maintain data pipelines using Apache NiFi, ensuring efficient ingestion and transformation. • Integrate structured and unstructured data from multiple sources, including Salesforce, APIs, SFTP, SAP, and CRM, into cloud-based and on-premise databases. • Ensure data quality, security, and governance across diverse sources and destinations. • Optimise and troubleshoot NiFi workflows to improve performance, reliability, and scalability. • Work with APIs to fetch and send real-time data for external integrations (e.g., CustomerGauge). • Manage and operate NiFi architecture within Kubernetes environments. • Collaborate with data scientists, analysts, and engineers to ensure data availability and usability. • Improve and optimise ETL/ELT processes for large-scale data processing. • Use NiFi Registry and Toolkit to maintain version control and streamline deployments across environments. • Develop Bash and Python scripts for automation, monitoring, and workflow execution. • Implement CI/CD pipelines for data pipeline deployments and workflow automation. • Analyse and resolve data pipeline issues, ensuring high availability and reliability.

• Architect, design, and manage end‑to‑end Snowflake‑based data platforms, ensuring high performance, scalability, and reliability • Lead data modelling initiatives (dimensional, normalised, and hybrid models) to support complex analytical and financial reporting needs • Design and implement ETL/ELT pipelines, including orchestration, data ingestion, and real‑time or near‑real‑time streaming integrations • Collaborate with stakeholders to analyse data requirements, translating business needs into effective data architecture designs. • Ensure best practices in Snowflake implementation, including performance optimisation, security, access control, and storage management. • Develop advanced SQL and Python scripts for data transformation, automation, and validation • Integrate DevOps practices such as CI/CD and infrastructure‑as‑code into the data engineering lifecycle • Provide architectural leadership and mentoring to data engineers, fostering high standards for delivery, documentation, and collaboration • Support proofs of concept (POCs) and contribute to technical evaluations of tools and technologies

• Participate in enterprise-scale migration projects from Hadoop/Hive to Snowflake; • Design and develop ETL/ELT pipelines for batch and near real-time ingestion; • Develop scalable and optimised Snowflake data models and transformations; • Work with technologies such as Snowflake, SQL, Python, PySpark, Snowpark, Spark, and Databricks; • Ensure data quality, consistency, governance, and security throughout migration activities; • Collaborate with architects, engineers, and business stakeholders across international teams; • Contribute to modernisation initiatives and cloud transformation programs; • Support continuous improvement and optimisation of enterprise data platforms.

• Architect, design, and manage end‑to‑end Snowflake‑based data platforms , ensuring high performance, scalability, and reliability • Lead data modelling initiatives (dimensional, normalized, and hybrid models) to support complex analytical and financial reporting needs • Design and implement ETL/ELT pipelines , including orchestration, data ingestion, and real‑time or near‑real‑time streaming integrations • Collaborate with stakeholders to analyse data requirements, translating business needs into effective data architecture designs. • Ensure best practices in Snowflake implementation , including performance optimisation, security, access control, and storage management. • Develop advanced SQL and Python scripts for data transformation, automation, and validation • Integrate DevOps practices such as CI/CD and infrastructure‑as‑code into the data engineering lifecycle • Provide architectural leadership and mentoring to data engineers, fostering high standards for delivery, documentation, and collaboration • Support proofs of concept (POCs) and contribute to technical evaluations of tools and technologies

• Design and implement scalable integrations (APIs, services, MCP interfaces) that expose internal and external systems as reusable skills for AI agents • Collaborate on the development and optimisation of the execution layer, ensuring reliable, secure, and scalable agent-driven actions • Integrate the AI platform with business systems such as GIS data sources, valuation tools, and other enterprise applications • Build and maintain clean, well-documented APIs and backend services supporting modular and reusable architectures • Ensure integrations are robust, observable, and performant, with appropriate monitoring and error handling • Work closely with AI and Data Engineers within a shared backlog, contributing to full end-to-end delivery rather than isolated components

• Design, develop, and maintain scalable data pipelines and backend services on Azure • Build and optimize data products and data platforms using modern lakehouse architectures • Develop and maintain APIs and integrations to connect internal and external systems • Ensure data quality, reliability, and performance across pipelines and services • Work with structured and unstructured data to support analytics and downstream systems • Contribute to CI/CD pipelines , automation, and deployment processes • Collaborate in a cross-functional Agile team , taking shared ownership of deliverables • Continuously improve solutions, standards, and team practices

• Develop and enhance Mendix applications, delivering high-quality solutions to real business problems • Translate business requirements into scalable and sustainable Mendix solutions • Collaborate closely with IT, business stakeholders, and Product Owners to refine and deliver features • Contribute to application maintenance and continuous improvement following DevOps principles • Ensure best practices in coding, security, and performance across all developments • Support and mentor junior developers, fostering team growth and knowledge sharing

• Design, build, and maintain AI-powered copilots and agents using Microsoft Copilot Studio for conversational, assistive, and autonomous scenarios • Develop end-to-end solutions using Power Platform components (Power Automate, Power Apps, Dataverse) to orchestrate workflows and business logic • Implement multi-step conversation flows, tool/function calling, and agent orchestration aligned with clear business outcomes • Apply data grounding and retrieval techniques (structured and unstructured data) to ensure accurate, reliable copilot responses • Integrate copilots and automations with enterprise systems using APIs, connectors, and Power Automate flows • Ensure solutions comply with enterprise standards for security, privacy, governance, and reliability within the Microsoft ecosystem • Manage the full lifecycle of copilots and automations: design, development, testing, deployment, monitoring, and continuous improvement • Collaborate closely with product owners and business stakeholders to translate use cases into scalable Power Platform and Copilot Studio solutions

• Develop and enhance Mendix applications, delivering high-quality solutions to real business problems • Translate business requirements into scalable and sustainable Mendix solutions • Collaborate closely with IT, business stakeholders, and Product Owners to refine and deliver features • Contribute to application maintenance and continuous improvement following DevOps principles • Ensure best practices in coding, security, and performance across all developments • Support and mentor junior developers, fostering team growth and knowledge sharing