Datatonic

Data Engineer

• Build the infrastructure that enables analytics and data science teams to deliver innovative, impactful solutions for clients.
• Assist clients in migrating their existing business intelligence and data warehouse solutions to Google Cloud.
• Develop, and optimize robust data pipelines, making data easily accessible for visualization and machine learning applications.
• Develop and implement new data warehouse and data mart solutions, including:
• - Transforming, testing, deploying, and documenting data.
• - Understanding data modeling techniques.
• - Optimising and storing data for warehouse technologies.
• Build, maintain, and troubleshoot cloud-based infrastructure to ensure high availability and performance.
• Work closely with technology partners such as Google Cloud, Snowflake, dbt, and Looker, mastering their technologies and building a network with their engineers.
• Collaborate in an agile and dynamic environment with a team of data engineers, BI analysts, data scientists, and machine learning experts.
• Implement software engineering best practices to analytics processes, such as version control, testing, and continuous integration.

• Foundational Support for Analytics and Data Science Teams: Build the infrastructure that enables analytics and data science teams to deliver innovative, impactful solutions for clients.
• Google Cloud Migration and Data Warehouse Solutions: Assist clients in migrating their existing business intelligence and data warehouse solutions to Google Cloud.
• Build Scalable Data Pipelines: Design, develop, and optimize robust data pipelines, making data easily accessible for visualization and machine learning applications.
• Design and Build Data Warehouses and Data Marts: Design and implement new data warehouse and data mart solutions, including:
• - Transforming, testing, deploying, and documenting data.
• - Understanding data modeling techniques.
• - Optimising and storing data for warehouse technologies.
• Manage Cloud Infrastructure: Architect, maintain, and troubleshoot cloud-based infrastructure to ensure high availability and performance.
• Collaboration with Technology Partners: Work closely with technology partners such as Google Cloud, Snowflake, dbt, and Looker, mastering their technologies and building a network with their engineers.
• Agile and Dynamic Team Collaboration: Collaborate in an agile and dynamic environment with a team of data engineers, BI analysts, data scientists, and machine learning experts.
• Applying Software Engineering Best Practices: Implement software engineering best practices to analytics processes, such as version control, testing, and continuous integration.

Senior Data Engineer

Human Resources

• Prepare, update, and manage employment contracts, annexes, and documentation in line with Croatian and EU labour laws
• Ensure compliance with labour regulations (working hours records, H&S, mandatory documentation, workplace postings)
• Maintain up-to-date internal policies and support mandatory training coordination
• Prepare documentation and coordinate meetings for employee relations matters
• Manage the full payroll process for Croatia and support payroll processes across other European locations
• Oversee timesheets and working hours registers, ensuring accuracy and legal compliance
• Collaborate with Finance and external payroll partners to guarantee correct and timely payments
• Manage benefits administration (e.g., supplementary health insurance) and support compensation reviews
• Maintain HRIS data integrity and process all employee lifecycle changes
• Deliver smooth, structured, legally compliant onboarding and offboarding processes
• Coordinate access, right-to-work checks, documentation, and induction scheduling
• Act as the first point of contact for routine HR questions (policies, benefits, leave, processes)
• Support relocations, EU mobility, and visa/permit administration when needed
• Provide administrative support for employee travel (booking accommodation, flights, documentation)
• Work closely with Legal, Finance, IT, and external partners to ensure streamlined and compliant operations across the region

HR Generalist

Cloud Engineer

• Engage with customers and prospects to provide pre & post sales architectural advice and thought leadership for machine learning, analytics, and data migration projects.
• Contribute to the design and implementation of enterprise-scale Data and AI projects.
• Introduce innovative ideas and approaches to enhance Datatonic’s capabilities and methodologies.
• Collaborate with sales teams to provide technical expertise during client engagements and help scope solutions for challenging requirements.
• Partner with GTM teams to create and refine new market-ready solutions with a focus on technical leadership and governance.
• Conduct architecture reviews for key clients, delivering actionable recommendations to senior stakeholders.
• Define and embed best practices into project delivery, ensuring quality and consistency across initiatives.
• Contribute to Datatonic’s internal knowledge base, including technical collateral and thought leadership materials.
• Work in a dynamic, agile environment alongside data scientists, machine learning experts, data analysts, and data engineers.
• Collaborate closely with partners such as Google to leverage their technologies effectively.
• Guide team members, fostering a culture of growth and innovation.

Senior Google Cloud Architect

DevOps Engineer

• Design, implement, and automate scalable and resilient CI/CD & DevOps pipelines on Google Cloud Platform, tailored to client-specific AI/ML and data engineering needs.
• Develop and maintain IaC pipelines using tools like Terraform to automate infrastructure provisioning and deployment on GCP, improving efficiency and consistency.
• Define and embed best practices into our internal processes to enhance the quality and consistency of our work
• Introduce innovative ideas and approaches to enhance Datatonic’s capabilities and methodologies
• Collaborate with sales teams to provide technical expertise during client engagements and help scope solutions for requirements
• Contribute to Datatonic’s internal knowledge base, including technical collateral and thought leadership materials
• Work in a dynamic, agile environment alongside data scientists, machine learning experts, data analysts, architects and data engineers
• Collaborate closely with partners such as Google to leverage their technologies effectively
• Guide team members, fostering a culture of growth and innovation
• Provide expert advice to customers on DevOps best practices
• Establish and enhance DevOps functions within clients’ organisations
• Engage with customers and project teams throughout the project development lifecycle to ensure seamless delivery

Senior DevOps Engineer

Machine Learning Engineer

• Develop Solutions with Reinforcement Learning at a large scale.
• Design and deploy RL solutions from data selection, model training, to productionization.
• Translate Requirements: Interpret vague requirements and develop models to solve real-world problems.
• Data Science: Conduct ML experiments using programming languages with machine learning libraries.
• Optimisation: Optimise ML/RL solutions for performance and scalability.
• Custom Code: Implement tailored ML/RL code to meet specific needs.
• RL Architecture Design: Create reinforcement learning architectures using Google Cloud tools and services.
• (Bonus!) Data Engineering: Ensure efficient data flow between databases and backend systems.
• (Bonus!) MLOps: Automate ML workflows, focusing on testing, reproducibility, and feature/metadata storage.
• (Bonus!) Engineering Software for Production: Build and deploy production-grade software for machine learning and data-driven solutions.

Data Engineer

Senior Data Engineer

HR Generalist

Senior Google Cloud Architect

Senior DevOps Engineer

Senior Machine Learning Engineer – Reinforcement Learning