{"id":1821611,"url":"https://alion.io/job/programming-com-ingeniero-de-datos","title":"Ingeniero de Datos","company":{"id":3806591,"name":"Programming.com","domain":"programming.com","url":"https://alion.io/company/programming-com","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"contractor","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mexico City, Mexico"],"countries":["MX"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":60000,"max":null,"currency":"MXN","period":"month","gross":null,"usd_annual":39684},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Dagster","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Prefect","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Apache Kafka","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"Flink","optional":true},{"name":"GCP","optional":true},{"name":"Great Expectations","optional":true},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-10-03T06:05:03Z","employer_posted_date":null,"last_verified_at":"2026-10-03T06:05:03Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"Role: Data Engineer\nLocation: Remote (Requires occasional travel)\n\nResponsibilities:\nBuild and operate robust data pipelines for ingestion, cleaning, and transformation using Databricks, Airflow, or Dagster. \nDevelop efficient ETL/ELT workflows in Python and SQL to support both batch and streaming workloads.\nCollaborate with ML and AI teams to deliver high-quality datasets for training, evaluation, and production features. \nModel and maintain structured data assets (Delta, Parquet, Iceberg) for reliability, versioning, and lineage tracking. \nImplement orchestration and monitoring schedule jobs, track dependencies, and automate recovery from failures. \nEnsure data quality and compliance through validation frameworks, schema enforcement, and audit logging. \nContribute to data platform evolution evaluate tools, standardize best practices, and improve developer experience. \nSupport performance and cost optimization across compute, storage, and orchestration systems.\nQualifications:\n36 years of experience as a Data Engineer or ETL Developer in a production environment. \nProficiency in Python and SQL; 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