• Design and develop CLI tools, scripts, and internal utilities to automate repetitive tasks across the data platform, including: • Pipeline execution and orchestration • Data governance workflows • Metadata synchronization • Environment setup and configuration • Test harness development • Automate workflows on Databricks, including: • Job deployment and scheduling • Environment provisioning • MLOps processes using APIs, Terraform, or Databricks SDK • Build and implement robust testing frameworks: • Integration testing for pipelines • End-to-end validation of ETL/ELT workflows • Testing and validation for ML inference workflows • Improve overall productivity, scalability, and reliability of the data and ML engineering ecosystem • Develop lightweight internal tools and dashboards using frameworks such as React, Streamlit, or similar technologies to: • Visualize data pipelines and workflows • Demonstrate model inference capabilities • Provide configuration and operational controls • Enable internal productivity monitoring and dashboards • Collaborate with cross-functional teams to identify automation opportunities and implement best practices

• Definir y poseer modelos de datos impulsados por el negocio para la elaboración de informes financieros • Actuar como enlace entre los interesados en Finanzas y los equipos de tecnología • Diseñar y supervisar flujos de datos de extremo a extremo

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.