Senior Data Engineer

Encardio Rite Group
Madrid, Spain
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience required
5 years minimum
Working hours
Regular working hours
Languages
English, Spanish

Tech stack

HTML JavaScript (Programming Language) PHP (Programming Language) Agile Methodology Artificial Intelligence Airflow Amazon Web Services Automation of Tests Cascading Style Sheets (CSS) Cloud Computing Cloud Engineering Software Quality
+47 more
Cyber Security Continuous Integration Cron Extract Transform Load (ETL) Data Visualization DevOps Django Web Framework Github Python (Programming Language) PostgreSQL Machine Learning Software Product Management Redis Power BI OpenAI Tensorflow Prometheus SAS (Software) Secure Coding Software Deployment Software Engineering SonarQube TypeScript Management of Software Versions Google Cloud Data Ingestion Google Data Studio Flask (Web Framework) Large Language Models Grafana Generative AI Backend Keras Agentic-AI Fastapi Pytest Containerization Scikit Learn Information Technology Data Analytics Low-code Ollama Machine Learning Operations Google Gemini Restful APIs Data Pipelines Docker

Job description

  • 5+ years leading technology strategy, engineering teams, and AI product delivery.
  • 6+ years designing and deploying production-grade AI and machine-learning solutions.
  • 5+ years with cloud platforms, DevOps, CI/CD, containerization, and data pipelines.
  • Experience managing multidisciplinary teams of up to 10 people.
  • Proven delivery of AI solutions within banking, financial services, healthcare, insurance, or real estate.
  • Experience working directly with enterprise customers and senior stakeholders.
  • Startup, co-founder, CTO, or technology-department-building experience is strongly preferred.

Ideal Experience Mix

  • 5+ years leading technology strategy, engineering teams, and AI product delivery.
  • 6+ years designing and deploying production-grade AI and machine-learning solutions.
  • 5+ years with cloud platforms, DevOps, CI/CD, containerization, and data pipelines.
  • Experience managing multidisciplinary teams of up to 10 people.
  • Proven delivery of AI solutions within banking, financial services, healthcare, insurance, or real estate.
  • Experience working directly with enterprise customers and senior stakeholders.
  • Startup, co-founder, CTO, or technology-department-building experience is strongly preferred.

Education

  • Double Degree in Mathematics and Computer Science, or an equivalent degree in Computer Science, Mathematics, Artificial Intelligence, Data Science, Engineering, or a closely related quantitative field.
  • Strong academic record preferred.
  • Professional fluency in English and Spanish.

Core Skills

Leadership and Strategy

  • Technology strategy and annual planning
  • Engineering and AI team leadership
  • Agile project and resource management
  • Technical recruitment, mentoring, and training
  • Project budgeting, costing, pricing, and cash-flow forecasting
  • Enterprise stakeholder and client management
  • Information security and ISO 27001 compliance

Artificial Intelligence and Machine Learning

  • Machine-learning model development and production deployment
  • Predictive modelling, lead scoring, attribution, and collections optimization
  • Generative AI and large language models
  • Voice and WhatsApp AI agents
  • AI workflow and proposal-generation agents
  • Model training, validation, monitoring, and versioning
  • Experiment tracking with MLflow
  • TensorFlow, Keras, scikit-learn, OpenAI, Anthropic, Gemini, Grok, and Ollama

Software Engineering

  • Advanced Python
  • TypeScript and JavaScript
  • PHP, HTML, and CSS
  • FastAPI, Flask, and Django
  • REST APIs and backend system design
  • Automated testing with pytest
  • Software-quality controls and SonarQube quality gates

MLOps, DevOps, and Cloud

  • CI/CD architecture and implementation
  • GitHub Actions and Google Cloud Build
  • Docker and Kubernetes
  • Argo Workflows and Apache Airflow
  • AWS and Google Cloud Platform
  • Cloud-native ETL pipelines
  • Model deployment, monitoring, and production support
  • Grafana and Prometheus

Data and Analytics

  • PostgreSQL, Redis, Supabase, and SAS
  • Power BI, Looker Studio, and data visualization
  • Data ingestion and transformation pipelines
  • Financial and operational reporting systems

Automation

  • n8n and Make
  • Cron jobs, event triggers, and workflow orchestration
  • Hybrid low-code and custom-developed automation systems

Key Responsibilities

  • Define and implement the annual technology roadmap in alignment with business objectives.
  • Lead AI, machine-learning, software-engineering, data, DevOps, and MLOps initiatives.
  • Design and deploy production AI solutions for enterprise customers.
  • Develop predictive models, generative-AI applications, conversational agents, and intelligent automation systems.
  • Establish scalable model-training, experiment-tracking, deployment, monitoring, and retraining processes.
  • Design and maintain cloud-native architectures across AWS and GCP.
  • Implement CI/CD pipelines, automated testing, code-quality controls, and secure development practices.
  • Lead multidisciplinary teams using agile methodologies.
  • Recruit, train, mentor, and develop technical talent.
  • Prepare project plans covering scope, resources, timelines, costs, risks, and commercial pricing.
  • Manage technical relationships with enterprise customers and communicate complex solutions to non-technical stakeholders.
  • Ensure compliance with ISO 27001 and information-security requirements throughout the AI development lifecycle.
  • Build internal systems for financial tracking, operational reporting, workflow automation, and proposal generation.
  • Evaluate emerging AI technologies and determine their suitability for customer and internal applications.

Requirements

  • 5+ years leading technology strategy, engineering teams, and AI product delivery.
  • 6+ years designing and deploying production-grade AI and machine-learning solutions.
  • 5+ years with cloud platforms, DevOps, CI/CD, containerization, and data pipelines.
  • Experience managing multidisciplinary teams of up to 10 people.
  • Proven delivery of AI solutions within banking, financial services, healthcare, insurance, or real estate.
  • Experience working directly with enterprise customers and senior stakeholders.
  • Startup, co-founder, CTO, or technology-department-building experience is strongly preferred.

Ideal Experience Mix

  • 5+ years leading technology strategy, engineering teams, and AI product delivery.
  • 6+ years designing and deploying production-grade AI and machine-learning solutions.
  • 5+ years with cloud platforms, DevOps, CI/CD, containerization, and data pipelines.
  • Experience managing multidisciplinary teams of up to 10 people.
  • Proven delivery of AI solutions within banking, financial services, healthcare, insurance, or real estate.
  • Experience working directly with enterprise customers and senior stakeholders.
  • Startup, co-founder, CTO, or technology-department-building experience is strongly preferred., * Double Degree in Mathematics and Computer Science, or an equivalent degree in Computer Science, Mathematics, Artificial Intelligence, Data Science, Engineering, or a closely related quantitative field.
  • Strong academic record preferred.
  • Professional fluency in English and Spanish.

Core Skills

Leadership and Strategy

  • Technology strategy and annual planning
  • Engineering and AI team leadership
  • Agile project and resource management
  • Technical recruitment, mentoring, and training
  • Project budgeting, costing, pricing, and cash-flow forecasting
  • Enterprise stakeholder and client management
  • Information security and ISO 27001 compliance

Artificial Intelligence and Machine Learning

  • Machine-learning model development and production deployment
  • Predictive modelling, lead scoring, attribution, and collections optimization
  • Generative AI and large language models
  • Voice and WhatsApp AI agents
  • AI workflow and proposal-generation agents
  • Model training, validation, monitoring, and versioning
  • Experiment tracking with MLflow
  • TensorFlow, Keras, scikit-learn, OpenAI, Anthropic, Gemini, Grok, and Ollama

Software Engineering

  • Advanced Python
  • TypeScript and JavaScript
  • PHP, HTML, and CSS
  • FastAPI, Flask, and Django
  • REST APIs and backend system design
  • Automated testing with pytest
  • Software-quality controls and SonarQube quality gates

MLOps, DevOps, and Cloud

  • CI/CD architecture and implementation
  • GitHub Actions and Google Cloud Build
  • Docker and Kubernetes
  • Argo Workflows and Apache Airflow
  • AWS and Google Cloud Platform
  • Cloud-native ETL pipelines
  • Model deployment, monitoring, and production support
  • Grafana and Prometheus

Data and Analytics

  • PostgreSQL, Redis, Supabase, and SAS
  • Power BI, Looker Studio, and data visualization
  • Data ingestion and transformation pipelines
  • Financial and operational reporting systems

Automation

  • n8n and Make
  • Cron jobs, event triggers, and workflow orchestration
  • Hybrid low-code and custom-developed automation systems

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