Data Engineer

Build and operatedata ingestion pipelines (ETL/ELT)from multiple sources (field programs, research datasets, epidemiological surveillance systems, partners, files, APIs). Design and maintaindata models and curated datasetsthat standardize entities, metrics, and definitions across projects. Ensuredata quality, reliability, and consistencythrough automated checks, monitoring, and basic observability. Decide how data isstructured, stored, and versionedto enable long-term reuse and scalability. Make dataavailable and easy to consumefor dashboards, reporting, and AI/ML use cases. Proactively guide business and project teams on data best practices, setting standards, shaping requirements, and influencing how data should be collected, structured, and used. Collaborate closely with stakeholders to translate needs intoscalable, maintainable data foundations. Technologies (examples - adapt to actual stack) Languages:SQL, Python Pipelines / orchestration:Airflow, Prefect, Dagster or similar Transformations:dbt or equivalent Storage:Data warehouse / lakehouse (e.g. Snowflake, BigQuery, Databricks, Synapse) Data quality / monitoring:Great Expectations, Soda, or similar BI / Dashboards:Power BI, Tableau, Looker or similar

A senior, hands-onData Engineerwith a strong ownership mindset, comfortable building and operatingcore data structures and pipelines. 5+ years of experience inData Engineering or Analytics Engineeringroles. StrongSQLand solidPython, with hands-on experience building and runningETL/ELT pipelinesin production. Proven experience integratingheterogeneous and diverse data sources(multiple systems, files, APIs, changing schemas, inconsistent identifiers). Good understanding ofdata modelingand analytical data structures, with the ability to standardize entities, metrics, and definitions across projects. Experience ensuringdata quality, reliability, and monitoring, including automated checks and basic observability. Comfortable making dataavailable for dashboards, reporting, and AI/ML use casesthrough curated, analytics-ready datasets. Able to work proactively with business and project teams,shaping requirements and setting data standardsrather than waiting for fully specified inputs. Spanishas the daily working language;Englishrequired for specific projects and international collaboration. Pragmatic, ownership-driven mindset, strong communication skills, and motivation to work onsocial and public-health impact projects.

Flexible start time from Monday to Friday Permanent contract. Life and accident insurance. Ticket restaurant Training and language learning platform Wellness platform with unlimited free psychologist sessions Cabify transportation service for employee use Development plans, internal mobility policy. Many more! xkdbapo COMMITMENT TO EQUAL OPPORTUNITIES The InsudPharma group is aware that business management must align with the needs and demands of society, and therefore assumes the commitment to equal opportunities and treatment between men and women, as stated in the current regulations on the matter - Organic Law ******, and we do not discriminate against any person on the grounds of ethnicity, religion, age, sex, nationality, marital status, affective or sexual orientation, gender identity or expression, disability, or any other personal or social circumstance.

AI Labs is Insud Pharma's transversal team forArtificial Intelligence, Data Science, and Machine Learning, working across the group to deliver production-ready data and AI solutions with real impact. The team operates across a wide range of areas, includingR&D and clinical data, global health and epidemiology, manufacturing and quality, supply chain and operations, and business analytics, partnering closely with business units, and external organizations. AI Labs combines strong engineering standards with pragmatic execution, focusing on building scalable AI-enabled solutions that move from experimentation to real-world adoption. Role Context This role will beprimarily focused on projects linked to Fundación Mundo Sano, an international organization dedicated to improving health and quality of life for vulnerable communities through research, innovation, and international cooperation (e.g. neglected diseases such as Chagas). The goal of this position is to ensure that data coming from multiple sources becomesavailable, consistent, reliable, and reusable, enabling dashboards, reporting, and AI/ML use cases. Due to the international nature of the projects, the role may involveoccasional travel to Latin America, Africa, or other regionsto work closely with local teams and better understand data generation on the ground. Role Objective Build and operate acoherent, well-structured data foundationfor Fundación Mundo Sano projects by owning thedata engineering layer end-to-end: ingestion, modeling, data quality, availability, monitoring, and data delivery for dashboards and AI enablement.