Data Scientist And Ai Engineer With Databricks
AI engineer at BIP's consulting Competence Centre in Madrid, designing end-to-end generative AI solutions for enterprise clients — building Databricks lakehouse data pipelines, RAG architectures, and LLM-powered applications using Python, PySpark, Postgres, and open-source models like Qwen.
- Compensation
- Not disclosed
- Location
- Madrid, Spain
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data science
- Posted
Skills
Must have
- Master's degree in Computer Engineering, Computer Science, Statistics, Data Science, AI, Telecommunications or related STEM discipline
- Strong quantitative mindset, analytical skills and problem-solving
- Solid programming experience in Python
- Hands-on experience with PySpark for distributed data processing
- Practical experience with Databricks: notebooks, jobs, clusters, Delta Lake, data pipelines
- Experience designing and implementing ETL/ELT pipelines in lakehouse or cloud data environments
- Strong knowledge of SQL and relational databases
- Hands-on experience with Postgres: data modeling, query design, integration with analytical/AI workloads
- Experience processing structured and unstructured data (text, documents, images, enterprise sources)
- Knowledge of Generative AI techniques and Large Language Models
- Hands-on experience with open-source LLMs, preferably Qwen or similar
- Experience building RAG solutions: embeddings, vector search, semantic search
- Knowledge of prompt engineering and LLM orchestration patterns
- Experience integrating AI models into applications, APIs, data workflows or business processes
- Experience with version control systems such as Git
- Understanding of model evaluation, data quality, monitoring and responsible AI principles
- Fluent professional proficiency in Spanish and English
Nice to have
- Fine-tuning or adapting LLMs with LoRA, QLoRA, PEFT or instruction tuning
- Experience with Hugging Face libraries and open-source AI ecosystem
- Experience with MLflow within Databricks (experiment tracking, model registry, deployment)
- Experience with vector databases/search (Databricks Vector Search, pgvector, Chroma DB, Qdrant, Pinecone, Elasticsearch)
- Experience with Postgres extensions for AI/analytics, especially pgvector
- Experience developing APIs or backend services with FastAPI
- Experience with cloud platforms (Azure, AWS, Google Cloud)
- Experience with managed AI services (Azure OpenAI, Azure AI Foundry, AWS Bedrock, Google Vertex AI)
- Experience with Docker and Kubernetes containerization and deployment
- Experience with orchestration tools (Airflow, Databricks Workflows, Azure Data Factory)
- Knowledge of SDLC, CI/CD and production-grade engineering practices
- Experience with Agile frameworks such as Scrum or Kanban
- Experience building AI agents, tool-using LLM applications or workflow automation
Full description
Location: Madrid, Spain Enter our world. Transform with us. What will be your challenge? Within our Competence Centre “x Tech”, BIP has built one of the largest communities of Data Scientists, Data Engineers and AI specialists in Europe. From our international hubs, including Spain, we coordinate multidisciplinary teams delivering advanced data and AI solutions to leading enterprise clients across industries. As part of the continuous growth of this dynamic team, we are looking for professionals with strong hands‑on experience in Generative AI, data engineering and scalable AI architectures, with Databricks as one of the core technologies of the stack. As an AI Engineer – Generative AI & Databricks at BIP, you will design and implement end‑to‑end AI solutions combining robust data pipelines, scalable lakehouse architectures and state‑of‑the‑art language models. You will work mainly with Python, Py Spark, Databricks, Postgres and open‑source LLMs such as Qwen, helping clients transform complex business needs into production‑ready AI systems. You will work in project environments where data may come from structured and unstructured sources, including databases, documents, text, images, video, audio and enterprise applications. Your role will be to process, enrich, model and activate this data through advanced analytics, retrieval‑augmented generation, language model integration and AI‑powered automation. Projects may range from building data pipelines and analytical foundations in Databricks, to implementing RAG architectures, adapting LLMs to specific business contexts, creating AI agents, deploying AI‑enabled applications and integrating AI capabilities into business workflows and enterprise systems. In addition to project delivery, you will actively contribute to our internal AI Community through technology scouting, reusable assets, solution design, best practices, accelerators and business development initiatives. Mandatory Requirements Master’s Degree in Computer Engineering, Mathematical Engineering, Computer Science, Statistics, Data Science, Artificial Intelligence, Telecommunications Engineering or related STEM disciplines;
Strong quantitative mindset, analytical skills and problem‑solving capabilities;
Solid programming experience in Python;
Strong hands‑on experience with Py Spark for distributed data processing;
Practical experience working with Databricks, including notebooks, jobs, clusters, Delta Lake and data pipeline development;
Experience designing and implementing ETL/ELT pipelines in lakehouse or cloud data environments;
Strong knowledge of SQLand relational databases;
Hands‑on experience with Postgres, including data modeling, query design and integration with analytical or AI workloads;
Experience processing structured and unstructured data, including text, documents, images or other enterprise data sources;