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Data Engineer
Data engineer at Hypercube Consulting, a fast-growing UK data-and-AI consultancy serving the energy sector. Day to day you turn client requirements into designs and build, test and deploy cloud data platforms and pipelines (Python, SQL, AWS/Azure/GCP, lakehouses) from event streaming to big data analytics, plus contribute to pre-sales and outreach.
Senior ML Engineer - Azure Data Platform & MLOps
Senior Machine Learning Engineer in The Hague on a small, highly technical team building an Azure-based data platform for finance, blockchain and digital assets. Owns the full data lifecycle — integrating sources, building pipelines, and developing and deploying production-ready ML models with MLOps practices.
Senior data ML engineer
Senior engineer in The Hague working across data engineering, ML and MLOps on an Azure data platform for an organisation focused on finance, blockchain and digital assets: building data pipelines, developing and deploying ML models, and automating deployment and monitoring. Core stack: Python, SQL, Azure ML, MLflow, CI/CD, Git.
Data Engineer Kapitaalmarkten
Data Engineer at the Dutch Authority for Financial Markets (AFM) designing, building and managing reliable data pipelines and datasets used for capital-markets supervision. Core stack: Azure cloud with Databricks, PySpark/SQL, Azure Data Factory, CI/CD via Azure DevOps, plus Unity Catalog, Declarative Automation Bundles and MLOps.
Senior Data Engineer
Senior Data Engineer / Data Architect building Change Data Capture (CDC) and data-ingestion pipelines in Databricks, Apache Spark, Delta Lake, and Azure, connecting sources like DB2, SQL Server, and Azure File Share to Kafka Confluent and SingleStore. Hybrid role based in Lisbon (Tagus Park), 3 days onsite per week.
Senior DevOps Engineer
Hands-on Senior DevOps engineer who owns Spotlite's infrastructure end to end on Azure: cloud architecture, CI/CD (GitHub Actions, Azure DevOps), data-pipeline orchestration (Dagster/Kestra), MLOps, DevSecOps and FinOps for geospatial satellite-imagery products, supporting Geospatial Data, ML, InSAR and Platform teams.
Python Software Developer | AI & Airflow
IT consultant role at Decskill in Portugal: developing, supporting, and monitoring conversational AI solutions — building REST APIs, RAG pipelines, and Airflow data pipelines, plus handling incidents, security remediation, and DevOps/MLOps collaboration. Core stack: Python, Airflow, Elasticsearch, and CI/CD tooling.
full stack developer for RAG platforms
Full-stack developer at IT consulting firm Extia building and operating RAG platforms: React frontends, Python backend services and data pipelines, APIGEE API integration, bot monitoring, incident follow-up and troubleshooting. Office role in Lisbon, working in Agile teams alongside MLOps, DevOps, security and product stakeholders.
Full Stack Developer (Python & React)
Inetum is hiring a full-stack developer (5+ years) to maintain and scale a strategic platform: building React frontends and Python backends, managing data pipelines and Apigee APIs, handling support and incident management, and collaborating with DevOps, MLOps, Data and Security teams. Hybrid role based in Lisbon, Portugal.
Lead Data Engineer (H/F)
Lead Data Engineer at Oventi, a Data & AI consulting firm in Paris: design medallion-architecture Lakehouse platforms, build ETL/ELT pipelines with SQL, Python, dbt and Spark, orchestrate with Airflow/Dagster, industrialize ML with MLOps and cloud IaC, while advising clients (CTO/CDO level) and mentoring engineers.
Forward Deployed Engineer (GenAI)
Forward Deployed Engineer (GenAI) at NTT DATA in Madrid: builds and deploys generative-AI prototypes, agents and automations for clients, translating business needs into working solutions alongside business consultants. Core stack: Python, LLMs, LangChain/LangGraph/CrewAI, RAG, vector databases, APIs and cloud.
AI & Data Engineer
Builds and industrializes batch and near-real-time data pipelines and AI/ML use cases (GenAI, agents) on CAF's internal Data & AI platform, applying DataOps/MLOps/LLMOps practices. Core stack: Python, SQL, Spark, AWS/Databricks, LangGraph and LLMs.
Mid-Level Machine Learning Engineer
Mid-level ML engineer building and deploying production machine learning systems end to end — model design, training, serving pipelines, and monitoring — for a San Francisco product team. Stack centers on Python, TensorFlow/PyTorch/scikit-learn, and MLOps tooling like SageMaker, Vertex AI, Kubernetes, and Docker.
Senior Data Scientist
Sber's Data Science team seeks a Senior Data Scientist to build GenAI initiatives for its bank-branch channel: taking multi-agent LLM systems, production RAG pipelines, model fine-tuning, evaluations and MLOps from prototype to production using Python, LangChain/LangGraph, Qdrant, Docker/k8s and vLLM/Triton inference.
Principal Data Engineer - QuantumBlack, AI by McKinsey
Principal Data Engineer at McKinsey's QuantumBlack in Santiago: leads technical teams and owns the tech stack for enterprise data and AI platforms. Day to day you architect scalable, reproducible ML data pipelines, mentor engineers, and collaborate with clients, using Python, Spark, cloud platforms, Databricks, and Airflow.
Analytics Engineer Melbourne, Victoria
Analytics Engineer at Bupa Australia in Melbourne, delivering and productionising data science, ML and analytics projects that improve health insurance customer outcomes. Day to day: building Azure data pipelines, feature stores and MLOps frameworks using SQL/TSQL, Python, Azure Synapse, Databricks/Spark and Power BI.
Analytics Engineer
Analytics Engineer at Bupa Australia in Melbourne delivering and productionising data science, ML and Gen AI projects for health-insurance customer analytics. Day to day involves building Azure data pipelines and reusable feature stores, implementing an MLOps framework, and working with SQL and Python on Azure services like Synapse, Databricks and Azure ML.
Analytics Engineer — Data Pipelines & ML Ops for Health
Analytics Engineer at Bupa Australia delivering and productionising data science and analytics projects that improve health insurance outcomes. The role involves migrating to a new Azure-based data platform, building an MLOps framework for propensity models, and creating scalable, reusable data assets and pipelines.