Role Description We are looking for Senior Data Engineers to join a project delivered for our international client operating in a data-intensive and technology-driven environment. The client is building modern real-time data platforms that power operational and near real-time business use cases such as logistics, tracking, fraud detection, customer interactions, and intelligent decision-making systems. This role is a great opportunity to work on large-scale event-driven architectures and streaming platforms processing high volumes of data with strict latency and reliability requirements. You will contribute to the design, development, and optimization of real-time data pipelines and distributed processing systems that enable business-critical applications and analytics capabilities. About project: - The project combines data engineering, distributed systems, cloud technologies, and streaming architectures within a collaborative international environment. - You will work closely with platform engineers, machine learning teams, product stakeholders, and other engineering disciplines to deliver scalable and reliable real-time data solutions. You will be: - Designing and implementing real-time data pipelines and streaming architectures. - Building, maintaining, and improving event-driven data processing systems. - Ensuring low-latency and high-throughput processing of streaming data at scale. - Integrating multiple internal and external data sources into streaming pipelines. - Implementing monitoring, alerting, logging, and observability solutions for real-time systems. - Ensuring data quality, consistency, and reliability within streaming environments. - Collaborating closely with platform, machine learning, and product teams on real-time business use cases. - Optimizing pipeline performance, scalability, and operational stability. - Participating in architecture discussions related to distributed systems and event-driven platforms. - Supporting troubleshooting, debugging, and continuous improvement activities across data processing environments. - Contributing to engineering best practices, automation, and operational excellence initiatives. - Depending on seniority, taking ownership of technical areas, supporting architectural decisions, and mentoring less experienced team members. Qualifications - 5+ years of commercial experience in Data Engineering or related disciplines. - Strong programming skills in Python, Java, or Scala. - Hands-on experience with streaming technologies such as Kafka, Kinesis, Google Pub/Sub, or similar platforms. - Proven experience building real-time or near real-time data pipelines. - Strong understanding of distributed systems and event-driven architecture principles. - Practical experience working with AWS cloud services. - Experience with modern data processing frameworks such as Apache Flink, Spark Streaming, or similar technologies. - Strong understanding of scalability, fault tolerance, and reliability in distributed environments. - Experience working with modern software engineering practices, testing approaches, and CI/CD workflows. - Strong problem-solving, communication, and collaboration skills. - Ability to work effectively in cross-functional and international teams. - Experience with stateful stream processing and windowing concepts. - Understanding of exactly-once and at-least-once processing semantics. - Familiarity with monitoring, observability, and operational tooling for streaming platforms. - Experience integrating streaming pipelines with downstream analytics, reporting, or machine learning solutions. - Exposure to containerization and orchestration technologies such as Docker and Kubernetes. - Practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery. - Work from the European Union region and a work permit are required. Requirements - Experience with unified batch and streaming platforms such as Databricks, Apache Beam, or similar technologies. - Knowledge of real-time machine learning feature pipelines and feature engineering workflows. - Experience working with high-scale event-driven systems processing millions of events per day. - Experience contributing to platform-level architecture and technical strategy. - Familiarity with data platform modernization and cloud-native architecture patterns. - Experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work. - Interest in and familiarity with emerging AI-driven practices (e.g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches. Recruitment Process - CV review - HR call - Interview - Client Interview - Decision

Role Description We’re looking for a Data Engineer (HR Support) to work on group data review and alignment, supporting group-wide People & Culture (HR) data consistency, reporting, and systems (e.g. SAP SuccessFactors). This role will involve close cooperation with the Group HR Controller, country HR Heads, project teams, and multiple other technical and non-technical stakeholders. Qualifications - Understands and can align data types, structures and validations with business context, processes and needs - Has previous experience in at least one system migration project with responsibility for data - Can query and analyze large and varied datasets, spot inconsistencies and patterns, and formulate conclusions using SQL, Python, Databricks, PowerBI, Excel, and GenAI - Can design and implement data processes, monitoring and governance solutions - Demonstrates awareness of GDPR / data privacy regulations - Is able to work with and understands the sensitivity of HR personal data - Can document findings clearly, including data dictionaries, field mapping, playbooks and process write-ups - Communicates data findings and recommendations to non-technical stakeholders in a clear and structured way - Has strong analytical skills, complemented by attention to detail and a high standard for data accuracy - Proficient in Polish and English (C1 or higher) Requirements - Previous experience working with data across multiple countries or legal entities - Practical experience with a global HRIS (HR Information System) - Knowledge of process mining or data-driven process improvement and/or hands-on process redesign experience - Lean Six Sigma certification (Green Belt / Black Belt) or BPM - Experience in building Power BI dashboards and views Benefits - An international, cross‑functional environment with experienced engineering leaders. - The opportunity to work on products used by millions of users across Europe. - Real ownership and influence over teams, technical direction, and long‑term solutions. - Flexible working model with remote options in Poland. - A strong engineering culture focused on quality, collaboration, and impact. - We offer a B2B contract.

Role Description Are you passionate about designing meaningful interactions between humans and data? Do you want to see your solutions directly improve patient care? In this position, you will develop next-generation data interaction for remote heart failure monitoring, working closely with clinicians, engineers, and industry in a hospital-driven environment. Data is everywhere, but turning data into actionable insights that people can effectively use remains a major challenge. In this EngD project, you will design, develop, and validate innovative data interaction solutions that enable users, ranging from engineers to clinicians, to make better, faster, and more informed decisions. You will work at the intersection of data science, human-computer interaction, and system design. Your goal is to create intuitive, robust, and user-centered solutions that bridge the gap between complex data models and the real-world application: remote heart failure monitoring. During this program, you will: - Design interactive systems that translate complex datasets into understandable and actionable insights. - Develop prototypes of interactive data science architecture and data-driven applications, including visualization dashboards and decision-support tools. - Explore AI-assisted data interaction. - Collaborate closely with industrial and clinical partners to ensure relevance and real-world impact. - Evaluate usability, effectiveness, and adoption of your designs through user studies and iterative refinement. - Integrate technical, human, and organizational perspectives into a coherent design solution. Your work contributes directly to societal challenges, such as improving healthcare decision-making, enhancing engineering workflows, and enabling responsible use of data in professional environments. Qualifications - A master’s degree (or an equivalent university degree) in Data Science, Computer Science, Human-Computer Interaction, Electrical Engineering, Biomedical Engineering, or a related field. - A design-oriented attitude with a strong interest in user-centered development. - Affinity with data visualization, interaction design, or decision support systems. - Ability to work in a team and interested in collaborating with industrial partners. - Strong analytical and problem-solving skills. - Fluent in spoken and written English. Requirements - Full-time employment for two years. - Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale TOIO (€ 3,029). - A year-end bonus of 8.3% and annual vacation pay of 8%. - Free access to a personal development program for EngD trainees. - An excellent technical infrastructure, on-campus children's day care and sports facilities. - Unlimited access to the modern on-campus TU/e Student Sports Center at an exceptionally affordable rate. - An allowance for commuting, working from home and internet costs. - A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates. Application We invite you to submit a complete application by using the apply button. The application should include: - A cover letter in which you describe your motivation and qualifications for the position. - A curriculum vitae, including a list of your publications and the contact information of three references. Kindly note that we may reach out to references at any stage of the recruitment process. We recommend notifying your references upon submitting your application. - Copies of relevant BSc and MSc diplomas and grade transcripts. - The result of an English proficiency test such as IELTS or TOEFL. Ensure that you submit all the requested application documents. Please note that incomplete applications may not be considered and could be rejected. We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled. Please note: You can apply online. We will not process applications sent by email and/or post.

• Lead the design, development and deployment of secure, scalable data pipelines and data platform components. • Design and implement batch and real-time streaming solutions using modern event-driven architectures. • Own technical design decisions across projects, balancing scalability, security, performance and delivery requirements. • Lead technical workshops, discovery sessions and architecture discussions with client stakeholders. • Assess existing client data platforms and design practical approaches for modernisation, migration and integration. • Build and maintain data ingestion, transformation and integration capabilities across a variety of data sources. • Develop cloud-native data platforms using AWS services and open-source technologies. • Ensure data quality, governance, lineage and security requirements are embedded throughout the data lifecycle. • Drive engineering best practices including code reviews, automated testing, CI/CD and Infrastructure as Code. • Support multiple client engagements, helping delivery teams maintain consistent engineering quality and standards. • Mentor and support engineers across project teams, providing technical guidance and leadership. • Perform data modelling, performance tuning and root cause analysis to resolve complex data and platform issues.