{"id":3138655,"url":"https://alion.io/job/unosquare-data-engineer-data","title":"Data Engineer Data","company":{"id":57940,"name":"Unosquare","domain":"unosquare.com","url":"https://alion.io/company/unosquare","size_band":"201-500","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Bolivia"],"countries":["BO"],"hiring_countries":["CO","MX","BO","PY"],"hiring_countries_total":4,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Grafana","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-21T17:13:40Z","employer_posted_date":null,"last_verified_at":"2026-10-21T17:13:40Z","board_verified":false,"closed_at":null,"days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"We are looking for a Data Engineer to build and maintain the data pipelines that turn raw data into stable, trusted datasets used to optimize performance. Working closely with Physics and Analytics Engineers, you will take exploratory and lab-built datasets and make them production-grade and shared across teams. The role suits someone who is comfortable going deep into technical detail while keeping the wider system in view. You should be able to turn scientific concepts into reliable, production-ready code and explain your work clearly to both technical and non-technical audiences.\n\nKey Responsibilities\n\nDesign, build, maintain and optimize data pipelines that transform raw data into stable, reliable datasets used for performance optimization.\n\nCollaborate closely with Physics and Analytics Engineers to understand data needs and turn them into production solutions.\n\nTurn lab and exploratory datasets into trusted, documented, shared datasets.\n\nTranslate scientific and analytical concepts into scalable, production-ready code.\n\nGather and clarify requirements with stakeholders, and confirm that delivered data meets their needs.\n\nLead or support incident response for data issues, including root cause analysis, troubleshooting and debugging across the pipeline.\n\nMonitor pipeline health and data quality, and build dashboards and alerts that make issues visible early.\n\nPresent findings, designs and status updates to technical and non-technical audiences.\n\nQualifications\n\nStrong data fundamentals: data modeling, data quality, ETL/ELT patterns and pipeline design.\n\nAdvanced proficiency in Python and SQL.\n\nHands-on experience with Spark and PySpark for large-scale data processing.\n\nExperience with Databricks.\n\nVersion control with Git, including collaborative branching and code review workflows.\n\nProven root cause analysis, troubleshooting and debugging skills in production data environments.\n\nAbility to move between detailed technical analysis and broader system context.\n\nStrong communication skills, especially for requirements gathering and incident response.\n\nStrong presentation skills.\n\nExperience with Grafana for monitoring and observability (preferred).\n\nBackground working with scientific, physics or engineering data (preferred).\n\nDesired criteria\nSQL, Python, git, spark, Pyspark, Grafana, 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