Data Platform | AI / ML | GCP | Direct HiringThe company you will work forEnhance situational awareness and decision-making across land, sea, and air through advanced data processing and analysis.Your New MissionArchitect and implement scalable infrastructure for data and machine learning workloads, leveraging modern cloud-native and on-premises distributed systems.Build and maintain robust, high-performance data pipelines to ingest, process, and store large-scale datasets from diverse sources.Administer and fine-tune databases and data warehouses to ensure high availability, data integrity, and optimal performance.Consolidate data from various origins—APIs, internal systems, and third-party providers—into unified, analysis-ready datasets.Develop tools and interfaces that empower business users and analysts to independently access insights and interact with ML models.Contribute to the evolution and scaling of the Data & AI Platform, supporting new use cases and capabilities.Uphold data governance standards, ensuring compliance with privacy regulations and implementing robust security practices.Establish validation and monitoring mechanisms to maintain data accuracy, consistency, and reliability across systems.Partner with data scientists, analysts, and engineering teams to understand platform needs and deliver tailored infrastructure solutions.Implement observability tools and performance tuning strategies to ensure system reliability, scalability, and cost-efficiency.Maintain clear, comprehensive documentation of data workflows, APIs, schemas, and ML systems to support onboarding and collaboration.What you need to be succeedBachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field (Mandatory).5+ years of experience in data & ML platform engineering or a similar role.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 and their data services, with a focus on Google Cloud.Familiarity with big data technologies (e.g.Spark),data warehousing solutions (e.g., Redshift, Snowflake), 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 scaleExperience 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 the company can offer youMeal AllowanceHealth InsuranceRemote Work ModelNext StepsIf you are interested in this opportunity, please send us your updated CV. If you are looking for a different kind of professional challenge, feel free to contact us to discuss other career opportunities — always in complete confidentiality.