• Lead data architecture design, API assessment, and ETL requirements gathering during the Discovery & Design phase. • Develop and configure CMIC ERP API integration to establish reliable data exchange between the ERP system and the AWS platform. • Design and implement data pipelines using AWS Glue for ETL processing of subcontractor documents and ERP data. • Integrate Amazon Textract to extract structured data from insurance certificates, bonding letters, and financial documents. • Build and maintain data models to support AI-powered validation, risk profiling, and executive reporting. • Configure Amazon S3 data lake architecture to store and manage raw, processed, and curated data assets. • Implement AWS Lambda and AWS Step Functions to orchestrate data workflows and automated processing pipelines. • Develop and expose data through Amazon API Gateway to support application and dashboard consumption. • Ensure data quality, validation, and integrity across all integration points and pipeline outputs. • Conduct data integration testing and support user acceptance testing (UAT) for data-dependent features. • Collaborate with Full Stack, AI/ML, and DevOps team members to ensure seamless end-to-end data flows. • Contribute to knowledge transfer documentation, data pipeline runbooks, and operations guides.

Dreamix was founded 19 years ago by passionate IT students who wanted to create the dreamiest workplace where everyone is heard, works under transparent management, and lives up to their full potential. Now, many years later, we deliver software solutions for renowned companies from Germany, the UK, Switzerland, and Silicon Valley. We believe that the employer-employee relationship must be in the form of partnership, not transaction. We are committed to investing as much as possible in our employees and we expect the same from you. About the Role: We are looking for a skilled and motivated Lead Data Engineer to drive the design, implementation, and evolution of cloud-native data platforms on AWS. In this role, you will own the end-to-end architecture of data ingestion, transformation, and delivery pipelines — from heterogeneous source systems through to executive-facing BI dashboards. You will combine deep technical expertise with strong stakeholder engagement to ensure data solutions are robust, scalable, and aligned with business needs. Responsibilities: - Lead teams of data engineers and analytics professionals, providing technical direction and mentorship across the project lifecycle - Architect and implement cloud-native data platforms on AWS, designing schemas and ingestion pipelines that handle structured data from diverse sources including Excel feeds, legacy databases, and third-party systems - Design, develop, and maintain ETL/ELT pipelines using AWS Glue and Step Functions, ensuring reliable data transformation, validation, and quality enforcement at every stage - Own the infrastructure-as-code practice using Terraform — provisioning, versioning, and managing all cloud resources with full reproducibility and environment consistency - Deliver end-to-end reporting solutions through Power BI, translating complex data models into intuitive dashboards that provide stakeholders with actionable, near-real-time insights - Translate complex technical concepts and architectural decisions to non-technical stakeholders clearly and persuasively, facilitating informed decision-making at all levels - Establish and enforce best practices around data quality, pipeline monitoring, documentation, and incident response - Participate in pre-sales and discovery efforts, leveraging technical expertise to support scoping, estimation, and business development initiatives Requirements: - Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field - 7+ years of experience in data engineering, cloud infrastructure, or platform development, with a demonstrated track record of delivering production-grade data solutions - Strong hands-on experience with AWS data services — particularly Glue, Step Functions, S3, RDS/Redshift, IAM, and CloudWatch - Proficiency in SQL and Python for data transformation, pipeline orchestration, and scripting - Solid experience with Terraform or equivalent IaC tooling for managing cloud infrastructure - Proven ability to design and optimize ETL/ELT pipelines for data ingestion from heterogeneous sources - Experience building dashboards and data models in Power BI (or equivalent BI tools such as Tableau or Looker) - Strong understanding of data modeling, schema design, and data warehousing concepts - Exceptional communication, presentation, and stakeholder management skills — comfortable leading technical discussions with engineering teams and presenting insights to C-level audiences alike - Strong leadership capabilities with experience mentoring engineers and driving best practices across teams Nice to Have: - Experience with additional AWS services such as Lambda, Athena, Lake Formation, or EventBridge - Familiarity with CI/CD pipelines for data infrastructure (e.g., GitHub Actions, CodePipeline) - Exposure to data governance, cataloging, or lineage tooling - Experience working in consulting or multi-client delivery environments What you’ll get: - A collaborative, knowledge-sharing culture built on transparency and mutual respect - Flexible working hours that allow you to balance your work and personal life - Unlimited home office to help you stay productive and focused - Opportunities for professional development, including certifications and training - Additional benefits for academic teaching and speaking engagements - Knowledge-sharing sessions where you can learn from our Dreamix team - Team and company-wide events that bring us together - Amazing week long summer office and winter office initiatives - Additional health insurance and dental allowance to ensure your well-being - Multisport card to encourage a healthy and active lifestyle - Office massages to help you relax and unwind If you find the mentioned above interesting, send us your CV! Only shortlisted candidates will be contacted. The confidentiality of all applications is assured! By applying for this job, you voluntarily agree and submit your personal information. Any personal data that you provide will be processed in strict confidentiality by Dreamix ltd. only for the purposes of selection and recruitment and will not be transferred to other data controllers unless required by law. It will be stored, processed, retrieved, and deleted in accordance with the GDPR.

• Join our world-class engineering team in building the Verisian Platform • Work on an application that exposes our clinical trial insights to various stakeholders • Support core modules targeting planning, exploration, building, validation, submission, and review of clinical trials • Analyze clinical trial documentation and turn them into actionable insights • Create data validation rules and develop a data analysis engine in Python to detect inconsistencies and errors • Lead analysis, design, building, and testing of components of the engine and data validation rules • Troubleshoot customer issues and deploy required fixes

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.