About the profileWe're looking for a Data Analyst and QA Engineer (Hybrid role) to join our Data and AI Engineering team. This role is ideal 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.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- 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 ForWe're committed to building a skilled and diverse engineering team. If you care deeply about writing clean code, delivering resilient systems, and collaborating across disciplines — this role is for you.Requirements - Must have- Data profiling: systematically assessing data quality across nulls, cardinality, distributions, min/max ranges, type consistency, and uniqueness.- Test planning & execution: defining test scope, writing test cases traceable to acceptance criteria, tracking defects, and coordinating UAT/regression cycles.- Strong documentation habits: process runbooks, incident write-ups, and analysis summaries, written with the traceability and version control expected in a regulated environment.- Experience with SQL for querying and manipulating relational databases.- Solid proficiency in Python for data analysis and manipulation (pandas, NumPy, matplotlib/seaborn), including exploratory data analysis and statistical techniques to uncover insights.- Demonstrable data-driven mindset: ability to ask the right questions, validate assumptions,



and support decisions with evidence.- Working knowledge of Power BI for building or maintaining dashboards and reports.- Understanding of data visualization principles and ability to communicate insights clearly to diverse audiences.- Team-first mindset and experience in agile environments (Scrum or Kanban).Requirements - Nice to have- Experience with clinical trial data, healthcare analytics, or regulated industry datasets.- Familiarity with advanced Python libraries (scikit-learn, stats models) for statistical modelling and machine learning.- Knowledge of Git/version control for collaborative analytics projects.- Experience with cloud platforms (Azure, AWS, or GCP) and cloud-native analytics tools such as Microsoft Fabric.- Exposure to agile analytics methodologies or analytics engineering principles.- Background with data governance, data quality frameworks, master data management, or GxP and other regulated industry standards.- Exposure to QA testing practices and defect tracking tools (e.G. Jira, Azure DevOps), plus basic anomaly detection methods (e.G. z-scores, IQR) for flagging unexpected values.Seniority Level- Middle / Senior.Languages- English: B2 / C1 level.- Spanish and/or Catalan language skills are nice to have.What we offer- Hybrid work model and versátil working schedule that would suit night owls and early birds.- 25 days of annual leave.- Opportunities for career development and the opportunity to shape the company's future.- An employee-centric culture directly inspired by employee feedback – your voice is heard, and your perspective encouraged.- Different training programs to support your personal and professional development.- Work in a fast-growing, international company.- Friendly atmosphere and supportive Management team.#J-18808-Ljbffr

📌 Data Analyst & Qa Engineer (Barcelona)
🏢 Tamarind Intelligence
📍 Barcelona