Data Scientist and AI Engineer with Databricks

• 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 PySpark for distributed data processing;
• Practical experience working with Databricks, including notebooks, clusters, Delta Lake and data pipeline development;
• 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, 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;
• Knowledge of Generative AI techniques and Large Language Models;
• Hands-on experience using open-source LLMs, preferably Qwen or similar model families;
• Experience building solutions based on Retrieval-Augmented Generation, embeddings, vector search and semantic search;
• Knowledge of prompt engineering techniques and LLM orchestration patterns;
• Experience integrating AI models into applications, APIs, data workflows or business processes;
• Experience with version control systems such as Git;
• Strong understanding of model evaluation, data quality, monitoring and responsible AI principles;
• Fluent professional proficiency in Spanish and English.

• Experience with Qwen or other open-source LLMs for enterprise AI use cases;
• Experience working with multimodal AI models for document, image, video or audio understanding;
• Experience fine-tuning or adapting LLMs using techniques such as LoRA, QLoRA, PEFT or instruction tuning;
• Experience with Hugging Face libraries, model repositories and open-source AI ecosystems;
• Experience with MLflow, particularly within Databricks, for experiment tracking, model registry and deployment lifecycle management;
• Experience with vector databases or vector search technologies such as Databricks Vector Search, pgvector, ChromaDB, Qdrant, Pinecone or Elasticsearch;
• Experience using Postgres extensions for AI or analytics workloads, especially pgvector;
• Experience developing data products, APIs or backend services using frameworks such as FastAPI;
• Experience with cloud platforms such as Azure, AWS or Google Cloud;
• Experience with Azure OpenAI, Azure AI Foundry, AWS Bedrock, Google Vertex AI or similar managed AI services;
• Experience with containerization and deployment tools such as Docker and Kubernetes;
• Experience with orchestration tools such as Airflow, Databricks Workflows, Azure Data Factory or similar;
• Knowledge of software development lifecycle, CI/CD and production-grade engineering practices;
• Experience working in Agile frameworks such as Scrum or Kanban;
• Experience building AI agents, tool-using LLM applications or workflow automation solutions;
• Experience with data governance, security, access control and privacy requirements in enterprise environments;
• Experience designing scalable data and AI architectures in cloud environments.

• Growth & Learning
• Access to 300+ courses on emerging technologies and business topics, personalized development programs, and continuous training initiatives to support your professional and personal growth.
• Flexibility & Work-Life Integration
• Hybrid working model with flexibility to balance remote and office work in agreement with your manager and project needs, plus initiatives supporting work-life balance.
• Health & Benefits
• Private health insurance, wellness platforms, meal vouchers, and an attractive benefits package.
• Family & Parenthood
• Support for new parents, including enhanced parental leave benefits and dedicated initiatives during and after parental leave.

Location: Madrid, Spain

Enter our world. Transform with us.

What will be your challenge?

Within our Competence Centre "xTech", 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, PySpark, 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.

• Strong consulting mindset;
• Ability to understand business problems and translate them into data and AI solutions;
• Excellent communication and interpersonal skills;
• Client-oriented and results-driven;
• Teamwork attitude and ability to collaborate with multidisciplinary teams;
• Curiosity and willingness to continuously explore new AI technologies;
• Attention to detail and ability to work under deadlines;
• Ability to explain complex technical concepts to both technical and non-technical stakeholders.