{"id":1318109,"url":"https://alion.io/job/zalo-senior-data-engineer-zalo","title":"Senior Data Engineer, Zalo","company":{"id":183385,"name":"Zalo","domain":"zalo.me","url":"https://alion.io/company/zalo-2","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":82,"open_postings":31,"ghost_share":0,"stale_share":0.516,"repost_share":0,"time_to_fill_p50_days":76,"computed_at":"2026-10-23T05:54:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Ho Chi Minh City, Vietnam"],"countries":["VN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":14000,"max_usd":36000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2491},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"dbt","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Great Expectations","optional":false},{"name":"Machine Learning","optional":false},{"name":"Pandas","optional":false},{"name":"Power BI","optional":false},{"name":"Prefect","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"SQLAlchemy","optional":false},{"name":"Superset","optional":false},{"name":"Tableau","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-08-17T00:00:00Z","employer_posted_date":"2026-09-26","last_verified_at":"2026-10-24T03:39:50Z","board_verified":true,"closed_at":null,"days_open":68,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":68},"description":"We are looking for a versatile Data Engineer who combines strong technical engineering capabilities with a Data Analyst mindset. In this hybrid role, you will do much more than build backend data pipelines - you will directly transform raw data into reliable business assets, build interactive dashboards for decision-makers, maintain strict Data Quality standards, and actively monitor Machine Learning models running in production.\nIf you enjoy working across the full data lifecycle - from raw ingestion to front-end visualization and ML performance tracking - this role offers a high-impact position within our data team.\nWhat you will do\nData Engineering & Pipeline Management\nDesign, construct, and maintain automated, scalable ETL/ELT data pipelines from diverse sources (SQL, NoSQL, APIs, Event Streams);\nArchitect and optimize Data Warehouse schemas or high-performance querying;\nAnalytics & Dashboarding (DA Focus)\nPartner with business and product teams to translate commercial requirements into clean, user-friendly Dashboards & Reports;\nBuild, publish, and maintain BI reports using tools like Superset, Power BI, Tableau;\nPerform ad-hoc data analysis to help business leaders answer critical strategic questions;\nData Quality & Governance\nImplement automated Data Quality validation frameworks to monitor accuracy, completeness, consistency, and data freshness;\nSet up real-time alerts for schema changes, pipeline failures, or abnormal data anomalies to minimize data downtime;\nML Performance & Drift Monitoring\nBuild telemetry pipelines to capture model predictions alongside real-world ground-truth outcomes;\nMonitor key ML metrics (Accuracy, Precision, Recall, AUC, Latency ...) and set up alerts for Data Drift and Concept Drift;\nCollaborate with Data Scientists/ML Engineers to flag performance degradation and trigger automated retraining loops.\nWhat you need\nCore Qualifications\n2-4+ years of hands-on experience in Data Engineering, Analytics Engineering, or a hybrid Data Analyst/Engineer role;\nStrong Programming & Querying: Advanced SQL (complex joins, CTEs, window functions, optimization) and Python (Pandas, PySpark, SQLAlchemy);\nData Warehousing & Orchestration: Direct experience with Onpremise Data Warehouses and orchestrators (Airflow, dbt, Prefect);\nBI & Data Visualization: Demonstrated experience crafting executive-ready dashboards in Superset, Power BI, Tableau;\nQuality & ML Monitoring Awareness: Familiarity with data testing tools (Great Expectations, dbt tests) and basic knowledge of Machine Learning evaluation metrics and monitoring concepts.\nSoft Skills & Mindset\nBusiness-to-Tech Translator: Ability to explain complex data architecture concepts to non-technical business partners clearly;\nData Ownership: High attention to detail with zero tolerance for silent data corruption or unmonitored failures;\nProblem-Solving Drive: A proactive attitude toward identifying process bottlenecks and automating repetitive analytics 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