Data Engineer

scalable, 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, Big Query, Databricks, Synapse) Data quality / monitoring: Great Expectations, Soda, or similar BI / Dashboards: Power BI, Tableau, Looker or similar Engineering basics: Git, CI/CD, basic cloud concepts (AWS / Azure / GCP) What we are looking for ~ A senior, hands-on Data Engineer with a strong ownership mindset, comfortable building and operating core data structures and pipelines . ~5+ years of experience in Data Engineering or Analytics Engineering roles. ~ Strong SQL and solid Python , with hands-on experience building and running ETL/ELT pipelines in production. ~ Proven experience integrating heterogeneous and diverse data sources (multiple systems, files, APIs, changing schemas, inconsistent identifiers). ~ Good understanding of data modeling and analytical data structures, with the ability to standardize entities, metrics, and definitions across projects. ~ Experience ensuring data quality, reliability, and monitoring , including automated checks and basic observability. ~ Comfortable making data available for dashboards, reporting, and AI/ML use cases through curated, analytics-ready datasets. ~ Able to work proactively with business and project teams, shaping requirements and setting data standards rather than waiting for fully specified inputs. ~ Spanish as the daily working language; English required for specific projects and international collaboration. ~ Pragmatic, ownership-driven mindset, strong communication skills, and motivation to work on social and public-health impact projects . Our benefits! Flexible start time from Monday to Friday Permanent contract.", "employmentType": "FULL_TIME", "industry": "Senior Engineer"

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