We’re looking for a Data Analyst and QA Engineer (Hybrid role) to join our Data and AI Engineering team. This role is adecuado for those with a quality-first mindset - passionate about profiling, testing, and safeguarding the integrity of data, while also uncovering patterns that drive business decisions and turning validated data into clear, data-driven narratives.

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You’ll safeguard data quality across life sciences projects - profiling datasets, running structured tests, and documenting findings to an audit-ready standard - while also working with cross-functional teams to translate validated data into clear, evidence-based insights for technical and non-technical stakeholders alike.

Responsibilities

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- Profile and analyse large datasets - assessing data quality (nulls, cardinality, distributions, uniqueness) and identifying trends, anomalies, and opportunities for optimisation or improvement.
- Design, execute,



and document structured test plans for data pipelines and dashboards, including defect tracking and reproducible results.
- Support data quality and governance initiatives by documenting data lineage, assumptions, methodologies, and incident write‑ups with the traceability expected in a regulated environment.
- Build ETL pipelines and data transformations using Python to prepare and process structured and unstructured data.
- Perform exploratory data analysis (EDA) and statistical analysis using Python (pandas, NumPy, SciPy, scikit-learn).
- Collaborate with Data Engineers and Business Stakeholders to understand analytical requirements and translate them into technical specifications.
- Present findings and recommendations to technical and non-technical audiences with clarity and impact.
- Maintain dashboards and reusable data models in Power BI to support self‑service reporting where needed.

What We’re Looking Fo

📌 Data Analyst (Barcelona)
🏢 MIGx
📍 Barcelona