Data Engineer

• Experience: 2+ years in data engineering or data science.
• AI-assisted engineering (essential): habitual and demonstrable use of an LLM-based code agent (Claude Code or equivalent) in real work, with the judgment to review what it produces. We do not expect you to have built agents; we expect you to already be working with one.
• Tech stack: Apache Airflow and BI tools (preferably Superset).
• Cloud: Google Cloud Platform, especially BigQuery.
• Programming: good level of SQL and data-oriented Python.
• Version control: demonstrable experience with Git/GitLab.
• Languages: fluent English, essential for daily work with the international team.
• Solid analytical and conceptual capacity.
• Ability to explain complex topics in a simple and understandable way.
• Autonomy, confidence in interpersonal dealings, and results orientation.
• A structured mind, capable of handling data architectures.
• Experience in the health and pharmaceutical sectors will be valued.
• Knowledge of other European languages will be valued.

• We value: MCP, LLM APIs, ClearML and Docker, Apache Druid, experience evaluating non-deterministic systems.

Atida is transforming the health and wellness sector in Europe. Our European markets operate on a single standardized data platform - the Foundation layer - and in 2027 our work is to make it usable not only by people, but by the AI agents that read it, reason about it, and act upon it.

You will be responsible for the data pipelines, datasets, AI agents, and tools built on Foundation, reporting directly to the Data & AI Engineer Lead, and you will build most of them with AI agents integrated into your work tools. The role is situated one level of abstraction above the code: you specify, review, and take responsibility for systems, instead of writing every line.

• Pipeline development: create and optimize data flows in Apache Airflow, from our European markets to BigQuery.
• Modeling in BigQuery: implement tables and views in the Foundation layer, ensuring KPI comparability between Spain, France, Italy, and Germany.
• Semantic layer and data contracts: maintain consistent business definitions across dashboards, models, and agents, and define the schema, granularity, and quality that a dataset guarantees.
• AI-assisted delivery: use Claude Code and the Anthropic API as your daily working environment - convert a requirement into a precise specification, let the agent produce the pipeline, and then review, test, and be accountable for the result.
• Building for agents: expose Foundation through MCP tools and skills so that AIDA and our decision agents can consult it reliably. A dataset is finished when an agent can use it without being misled.
• Evaluation: build the evals, controls, and monitoring that tell us if an agent's output is correct. Unit tests are not enough in non-deterministic systems.
• Data products: design data products for management, finance, commercial, operations, and marketing, reusable across all markets.
• Visualization and reporting: collaborate with the business team on reports and datasets consumable in Apache Superset.
• Code and traceability: clean Python and SQL, with every task traceable through our GitLab-Coda integration. Including code generated by an agent.

• Freedom to shape your role from day one: a position of responsibility with real growth opportunities, where you can proactively drive initiatives and actively contribute to defining the strategy.
• Permanent full-time contract: long-term perspectives in a market of the future.
• Agile working environment: a motivated and dynamic team, with flat hierarchies and decisions made fast enough to take action.
• Flexibility with team spirit: flexible schedule and hybrid model (remote and in-person) - with a focus on our Albacete office to foster collaboration and team cohesion.
• Direct mentorship from the Data & AI Engineer Lead in a technically demanding environment.
• Real exposure to Airflow, BigQuery, Druid, GCP, and a production AI stack (Claude, MCP, agents, evals) - the systems upon which the company operates.
• Professional AI engineering tools as standard equipment.

• Someone who delivers code they cannot explain.
• Someone who needs a ticket with the solution already inside or with all requirements closed. We move fast: we give you the problem, the context, and the access - you propose the design.
• Someone who uses AI as a shortcut and does not understand the problem they are solving.
• Someone who only looks at the short term. We build solutions prepared for the future.