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Russell Tobin is hiring a Data Engineer in Madrid to build scalable data solutions and pipelines for advanced analytics, working with big-data technologies like Hadoop and Spark. Requires 4+ years of hands-on experience and proficiency in Python, Java, SQL, and Scala, collaborating with technical teams and clients.
Split junior role at Sagacity in the UK: handle helpdesk support (ticket triage and escalation) while designing and maintaining scalable data pipelines, data integrations, and APIs, working with analysts, scientists, and stakeholders. Involves cloud services, big data tools, data quality, and secure storage.
Senior SAP TM Architect/Consultant who designs, configures, and implements SAP Transportation Management solutions (freight order management, freight settlement, charge management, planning) and integrates them with SAP ECC/S/4HANA, EWM, EM, and GTS. Full-time or contractor, remote anywhere in Europe.
Medior/senior Data Engineer at a Dutch IT consultancy and training institute near Amsterdam: you build and maintain data pipelines for clients (including banks and health insurers) and mentor junior engineers on the job and via internal trainings. Core stack centers on cloud (AWS/Azure), Python/SQL and big data tooling.
Staff AI Engineer at Relativity, whose AI-powered cloud platform RelativityOne serves legal eDiscovery. The role defines the multi-year MLOps roadmap, architects scalable training, inference, and monitoring systems on AWS/Azure/GCP (Python/Java/Scala, Docker/Kubernetes, Terraform, Airflow/Prefect), and mentors engineers across teams.
Senior backend engineer on Bitsight's Third Party Risk Management team, owning features from design through delivery of a SaaS product. Core stack is Python (Django/FastAPI/Flask, SQLAlchemy) with REST APIs, CI/CD, Docker/Kubernetes, and AWS.
Data Architect for MSI, an insurance MGA under the Baldwin Group, designing the enterprise data estate — lakehouses, data warehouses, and integrations — in partnership with BI, DBAs, and solution architects to support analytics and data science. Core stack: Azure, Azure SQL, Microsoft Fabric, and Spark/PySpark.
Senior data scientist on Navan's (TripActions) Fraud Risk Management team, designing and deploying ML models, anomaly/graph detection, and rule workflows to detect and prevent fraud across travel and expense card payments. Core stack: Python, SQL, modern ML libraries, and big-data platforms like Snowflake, Databricks, and Spark.
Platform engineer on OCBC's enterprise data team, administering the bank's Data, Analytics and AI/ML platforms — Cloudera CDP/CML, Hadoop and Spark across hybrid AWS and on-premises infrastructure, plus Kubernetes/OpenShift and AWS AI services. Day to day: platform upgrades, security patching, monitoring, troubleshooting, and automation with Python/Shell.
Database engineer at M2 Technology Group supporting critical national-security solutions at Fort Meade: designing and tuning MongoDB deployments, automating security monitoring, building data parsers/loaders, and developing Python microservices with Django/Flask. Requires an active NSA TS/SCI clearance with polygraph; salary $180k–$230k.
Builds and operates production data pipelines for reports, analytics and machine learning at Schwarz Group's Barcelona IT hub, ensuring data quality, security and scalability while monitoring and troubleshooting data infrastructure. Core stack: cloud (ideally Azure), Kubernetes, Spark, SQL and Python/Scala/Java in agile teams.
Data engineer at Schneider Electric in Barcelona who migrates Secure Power's legacy SQL- and Alteryx-based datasets and transformation workflows onto the company's next-generation cloud data lake (IDS Next), rebuilding and optimizing pipelines, validating data quality, and shaping the future analytical layer. Core tools: SQL, Alteryx, Tableau, and AWS.
Backend developer at consulting firm Talan building and maintaining business-critical data/backend solutions with Apache Spark and Scala in an Agile squad, covering the full lifecycle from user stories and coding to testing, UAT support, and production validation; key stack also includes PL/SQL and Control-M.
Data Engineer at PTSB, a leading Irish retail and SME bank, designing, building, and testing ETL pipelines and data engineering solutions to turn raw data into analytics-ready datasets. Core stack includes Teradata/Snowflake, Python, SQL, NoSQL, and big data tools; permanent hybrid role based in Dublin or Cork.
Data Engineer at PTSB (an Irish bank) who designs and optimises ETL processes, builds analytics-ready datasets, and models data across Teradata Vantage, Snowflake and modern big data tools. A Dublin/Cork hybrid role collaborating with Build and Run teams to support the bank's data-driven decisions.
Data Engineer in Auxilion's Business Enablement Solutions Practice, building cloud data management solutions for clients across industries. Day-to-day: designing ETL/data pipelines, integrating and modelling data, ensuring data quality, and delivering Power BI reports, using the Microsoft stack (Fabric, Azure Data Factory, Synapse, SQL Server).
Data Engineer (Run) at PTSB, a leading Irish retail and SME bank, building and maintaining ETL pipelines and analytics datasets while resolving data quality issues in a hybrid role based in Dublin/Cork. Core tech includes Teradata Vantage/EDW and Snowflake, Python, SQL, NoSQL, big data tools (Hadoop, Spark) and cloud platforms (AWS/Azure).
Software Engineer (Data/AI) at Data Surge in Los Angeles, developing and maintaining software and web applications, designing scalable, testable code, and fixing bugs. Requires US citizenship and experience with Python, SQL/Databricks, and AI development, AI governance, or Responsible AI.
Senior AI/ML Engineer on RBC's Global Payments Technology team, building LLM-powered AI agents for payments use cases like anomaly detection and process automation. Day-to-day involves training models, preprocessing data, and deploying/monitoring models in production using Python, TensorFlow/PyTorch, and frameworks like LangChain.
Senior data scientist at Wenco (a Hitachi Construction Machinery subsidiary) developing the data science strategy for mining technology: analyzing sensor and equipment time-series data, building predictive-maintenance models (anomaly detection, RUL), and visualizing insights for stakeholders. On-site in Richmond, BC, using Python/R, ML frameworks, and big-data tooling.
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