• Design, build, and maintain scalable data pipelines for both real-time and historical data processing. • Develop and optimize databases, data warehouses, and ETL workflows handling large-scale time-series data. • Process and manage high-volume data streams (thousands of records per second). • Collaborate with Product, Customer Success, Installation, and Technical Support teams to ensure data quality and business alignment. • Implement monitoring, alerting, and logging systems to ensure platform reliability. • Support Data Science teams by improving data accessibility and facilitating model deployment. • Troubleshoot and optimize data infrastructure performance.

Role Description At InPost, Data & AI is not a support function — it is the engine behind our decisions. We process billions of events daily across nine European markets, and our data platform is what makes that intelligence possible. As a Data Engineer in our Data & AI area, you will be one of the builders: designing the pipelines, streaming systems, and lake architectures that turn raw operational data into reliable, high-quality data products powering ML models, analytics, and business decisions. You will work in cross-functional squads alongside Data Scientists, Analytics Engineers, and Product Managers, shipping real data products — not internal tooling that no one sees. The scale is real, the data is complex, and the impact is immediate. Success looks like: - Data products that are trusted, fresh, and easy to consume - Pipelines that run reliably at scale with no manual intervention - A codebase that your colleagues are proud to contribute to Main Activities: - Data Platform & Lake Engineering: Design, build, and maintain scalable data lake solutions and processing pipelines handling large volumes of structured and semi-structured data. - Streaming Solutions: Build and operate real-time data streaming pipelines using Apache Kafka and its ecosystem (Kafka Streams, Kafka Connect). - ETL/ELT Design and Maintenance: Architect and maintain ETL and ELT pipelines with a focus on data quality, idempotency, and observability. - Spark and Databricks Development: Develop distributed data processing applications using Apache Spark (PySpark, Scala), running on Databricks. - Database Engineering: Design and manage both SQL and NoSQL databases used in our data products. - Cloud-Native Solutions: Build data solutions on cloud infrastructure (GCP, Azure, or AWS). - CI/CD and Engineering Excellence: Apply software engineering best practices to data pipelines. - Performance Monitoring and Optimisation: Own the operational health of the data infrastructure and ETL processes you build. - API and System Integration: Integrate data from internal and external sources via REST and SOAP APIs. - Knowledge Sharing and Community: Actively contribute to InPost's data engineering community. Qualifications - At least 3 years of experience in a Data Engineering or similar role - Hands-on experience with Apache Spark (Streaming, Spark SQL, MLlib) and Databricks (PySpark, Scala) - Practical experience with Apache Kafka — including Kafka Streams and Kafka Connect - Proficiency in Python; working knowledge of Scala or Java - Experience designing and operating SQL databases (e.g., PostgreSQL, BigQuery, Spark SQL) and NoSQL databases (e.g., MongoDB, Cassandra, or similar) - Experience building and maintaining data lake environments (Delta Lake, Parquet, or equivalent) - Familiarity with cloud platforms (GCP, Azure, or AWS) and their managed data services - Experience integrating data via REST and/or SOAP APIs - Working knowledge of CI/CD tooling (GitLab CI, Jenkins, or equivalent) and software engineering practices (testing, versioning, code review) - Experience building and running Docker containers - Willingness to share knowledge and actively contribute to engineering best practices - Professional working proficiency in both English and Polish Requirements - Experience in an international, multi-market environment - Exposure to ML pipeline engineering or feature store design - Familiarity with data orchestration tools (Apache Airflow, Prefect, or Databricks Workflows) - Experience with Infrastructure as Code (Terraform, Ansible) - Contributions to open-source data engineering projects Benefits - The option to work from the office or 100% remotely - Opportunity to work in a diverse, international and cross-functional environment, along with leading experts - Fulfilling careers with a range of benefits for employees and invests in providing training opportunities for their development - Involvement in technology monitoring and choices - Your impact will be visible instantly and you will be making a difference in our users' lives

Role Description We are looking for an experienced Senior Data Engineer to join a fast-growing technology company building data-driven solutions at scale. In this role, you will design and maintain robust data infrastructure, process high-volume real-time data streams, and collaborate with cross-functional teams to support analytics and machine learning initiatives. 📍 Location: Philippines (Remote) 💰 Salary: Negotiable 📈 Seniority: Senior Level (5-10 years of experience) Key Responsibilities - Design, build, and maintain scalable data pipelines for both real-time and historical data processing. - Develop and optimize databases, data warehouses, and ETL workflows handling large-scale time-series data. - Process and manage high-volume data streams (thousands of records per second). - Collaborate with Product, Customer Success, Installation, and Technical Support teams to ensure data quality and business alignment. - Implement monitoring, alerting, and logging systems to ensure platform reliability. - Support Data Science teams by improving data accessibility and facilitating model deployment. - Troubleshoot and optimize data infrastructure performance. Qualifications - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. - 5+ years of experience as a Data Engineer. - Strong experience designing and scaling data infrastructure. - Hands-on experience working with time-series data. - Expert-level SQL skills, especially PostgreSQL and PL/pgSQL. - Ability to analyze and optimize database query execution plans. - Experience with ETL and data pipeline tools such as Airflow, Metaflow, or similar platforms. - Experience with TimescaleDB or other time-series databases. - Strong Python programming skills. - Understanding of data warehousing concepts and best practices. Preferred Qualifications - Excellent problem-solving skills. - Self-driven, proactive, and quick learner. - Experience supporting data science and machine learning workflows. Benefits - Fully remote working environment. - Opportunity to work with cutting-edge data technologies. - Collaborative international team. - Competitive compensation package. - Performance-based incentives. - Comprehensive benefits package. - Strong focus on learning, development, and career growth. - Flexible and autonomous working culture. Recruitment Process - HR Interview - Hiring Manager Interview - Take-home Assignment - Culture Fit Interview

Role Description Für unseren Kunden aus der Gesundheitsbranche in Bern, suchen wir eine:n erfahrene:n, motivierte:n und aufgeschlossene:n ETL Datenbank Entwickler:in. Zur Verstärkung des Teams wird eine erfahrene Persönlichkeit gesucht, die mit fundiertem Know-how in ETL-Engineering bei der Integration und Weiterentwicklung moderner Datenlandschaften unterstützt. - Konzeption, Implementierung und kontinuierliche Weiterentwicklung von ETL-Ladestrecken - Anbindung und Integration neuer Quellsysteme in ein MS SQL-basiertes Data Warehouse - Entwicklung, Deployment und Betrieb von ETL-Prozessen mit SSIS - Transformation und Harmonisierung von Daten aus unterschiedlichen Quellen - Mitwirkung bei der Weiterentwicklung der bestehenden DWH-Architektur - Unterstützung bei der Sicherstellung von Datenqualität und Performance - Analyse und Behebung von Fehlern in ETL-Prozessen sowie Monitoring der Datenflüsse Qualifications - Mehrjährige Erfahrung im Bereich Data Warehousing und ETL-Entwicklung - Sehr gute SQL-Kenntnisse im Microsoft SQL Server Umfeld - Fundierte Erfahrung mit SSIS (Entwicklung, Deployment und Betrieb) - Praxis in der Integration und Transformation heterogener Datenquellen - Gute Kenntnisse in der Datenmodellierung für DWH- und Reporting-Lösungen - Erfahrung im Monitoring sowie in der Fehleranalyse von ETL-Prozessen - Kenntnisse in BIML von Vorteil - Branchenkenntnisse im Gesundheitswesen oder Erfahrung mit klinischen Daten von Vorteil - Verhandlungssichere Deutschkenntnisse zwingend Company Description Die Coopers Group AG ist eine agile Schweizer Recruiting Agentur, die Spezialisten und Führungskräfte in den Bereichen IT, Life Sciences, Engineering und Finance vermittelt. Mit flexiblen Ansätzen bringen wir Kandidat:innen und Unternehmen zusammen, die nicht nur fachlich, sondern auch menschlich zusammenpassen.