Are you ready to revolutionise the world with TEKEVER? 🚀🌍 At TEKEVER, we lead innovation in Europe as the European leader in unmanned technology, where cutting-edge advancements meet unparalleled innovation. 💻 Digital | 🛡️ Defence | 🔒 Security | 🛰️ Space We operate across four strategic areas, combining artificial intelligence, systems engineering, data science, and aerospace technology to tackle global challenges — from protecting people and critical infrastructure to exploring space. We offer a unique surveillance-as-a-service solution that delivers real-time intelligence, enhancing maritime safety and saving lives. Our products and services support strategic and operational decisions in the most demanding environments — whether at sea, on land, in space, or in cyberspace. 🌐 Become part of a dynamic, multidisciplinary, and mission-driven team that is transforming maritime surveillance and redefining global safety standards. At TEKEVER, our mission is to provide limitless support through mission-oriented game-changers, delivering the right information at the right time to empower critical decision-making. If you're passionate about technology and eager to shape the future — TEKEVER is the place for you. 👇🏻🎯 Mission: As a Data & ML Platform Engineer, you will play a critical role in designing, building and maintaining the infrastructure that powers our data processing pipelines and machine learning workflows that support our data-driven initiatives, as well as supporting the evolution of our Data & AI Platform. You will work at the intersection of data engineering, MLOps, and platform development and ensure that our data & AI infrastructure is robust, scalable and efficient. The ideal candidate will have a strong background in platform engineering, with experience in data science, machine learning and or data engineering. What will be your responsibilities: - Data and ML infrastructure: Design and implement scalable data and ML infrastructure using modern cloud and on-prem distributed technologies and frameworks. - Data Pipeline Development: Design, develop and maintain scalable and efficient data pipelines to collect, process and store large volumes of data from various sources. - Database Management: Manage and optimize databases and data warehouses to ensure data integrity, performance and availability. - Data Integration: Integrate data from multiple sources, including APIs, databases and external data providers, to create unified datasets for analysis. - Self-Service Tools: Develop self-service tools that enable stakeholders to extract insights from Data and Machine Learning models. - Data & AI Platform development & expansion: support the expansion of our Data & AI Platform. - Security & Compliance: Ensure data security, privacy, and compliance. - Data Quality Assurance: Implement data validation and quality assurance processes to ensure the accuracy and consistency of data. - Collaboration: Work closely with data scientists, analysts and other stakeholders to understand platform requirements and provide the necessary data infrastructure and support. - Monitoring & Performance Optimization: Implement monitoring, observability, and alerting for data and ML systems and optimize for performance, reliability, and cost-effectiveness. - Documentation: Maintain comprehensive documentation of platform components, APIs, and workflows to ensure knowledge sharing and user adoption (e.g. data pipelines, database schemas, Machine Learning systems, etc.) Profile and requirements: - Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field. - Preferred location of working: UK, Portugal , France and/or Spain - Experience: 3+ years of experience in data & ML platform engineering or a similar role. - Analytical Skills: Strong analytical and problem-solving skills with a focus on delivering scalable and efficient data solutions. - Communication: Excellent verbal and written communication skills, with the ability to effectively collaborate with technical and non-technical stakeholders. - Language Requirements: Advanced proficiency in Portuguese and English, with proven fluency at the C2 level in both languages. - Attention to Detail: High attention to detail and a commitment to ensuring data quality and accuracy. - Adaptability: Ability to work in a fast-paced, dynamic environment and manage multiple priorities simultaneously. Technical Skills: - Proficiency in programming languages such as Python, Go, Java, or Rust. - Strong knowledge of containerization technologies (e.g. Docker) and orchestration systems (e.g. Kubernetes) in production environments. - Experience with SQL,database management systems (e.g., MySQL, PostgreSQL, SQL Server), data modeling and schema design. - Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services, with a focus on Google Cloud. - Familiarity with big data technologies (e.g. Spark), data warehousing solutions, data pipeline orchestration (e.g. Airflow), and database systems (SQL and noSQL). - Design and manage MLOps pipelines to support model training, deployment and monitoring at scale. - Experience implementing observability stacks and logging pipelines (e.g., Prometheus, Grafana, Loki, ELK). - Experience with IaC frameworks (e.g. Ansible, Terraform), - Understanding of DevOps best practices and tools: GIT, CI/CD, telemetry and monitoring, etc. What we have to offer you: - An excellent work environment and an opportunity to make a difference; - Salary Compatible with the level of proven experience.

• Design and Build new data solutions. • Design, Build and Maintain ELT Solutions. • Deliver Data Insights to colleagues and customers. • Resolve Bugs and Handle production Outages/issues. • Estimate Features/Bugs and Refine feature requirements delivered by product managers. • Carry out code reviews and maintain code quality. • Stay updated with the latest technologies and suggest improvements.

• Contribuir en la evolución de plataforma de datos corporativa. • Participar en el diseño, desarrollo y mantenimiento de soluciones modernas en AWS. • Construcción de pipelines confiables. • Migración de procesos legacy. • Soporte a una arquitectura Lakehouse. • Asegurar calidad, eficiencia y disponibilidad de los datos.

• 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