Data Engineer

Data Engineer (Mid/Senior)Level: 2–4 years experience | Location: Hanoi (Hoa Lac) | Language: English (Business Proficiency) | Type: Full-timeJob Description1. Data Pipeline & IntegrationDesign, build, and maintain scalable ETL/ELT pipelines (batch & streaming)Integrate data from diverse sources: databases, APIs, event streams, flat filesDevelop ingestion workflows using Airflow, Spark, KafkaEnsure data quality, consistency, and completeness2. Data Modeling & WarehouseDesign dimensional data models (star/snowflake schema)Build and maintain data warehouse/lakehouse on cloud (Redshift, Synapse, BigQuery, Databricks)Define data standards: naming conventions, data dictionaries, lineageOptimize query performance (partitioning, clustering, indexing, materialized views)3. Data Infrastructure & MLOps SupportManage data infrastructure using IaC (Terraform, CloudFormation)Build feature stores and pipelines feeding AI/ML modelsImplement data observability: SLA tracking, anomaly detection, drift alertsSupport CI/CD for data pipelines4. Collaboration & CommunicationWork with AI Engineers, Solution Architects, and Business Analysts to define data requirementsCommunicate architecture decisions clearly in EnglishParticipate in Agile/Scrum ceremonies (planning, stand-up, demo, retro)Maintain documentation: data catalogs, runbooks, data contractsQualificationsMust-Have:2–3+ years of hands-on data engineering experience in production environmentsProficiency in SQL (complex queries, window functions, performance tuning) and Python (pandas, PySpark)Experience with at least one orchestration framework (Airflow, Prefect, Dagster)Hands-on experience with a cloud data warehouse/lakehouse (BigQuery, Redshift, Synapse, Databricks)Understanding of data modeling: normalization, dimensional modeling, SCDEnglish proficiency — able to run technical meetings and write documentationUnderstanding of SDLC: Git workflow, code review, CI/CD, Agile/ScrumNice-to-Have:Experience with streaming platforms: Kafka, Kinesis, Event HubsFamiliarity with dbt for transformation layerKnowledge of lakehouse architecture: Delta Lake, Iceberg, HudiMLOps exposure: feature pipelines, training dataset managementExperience in retail/e-commerce/SaaS domain (transaction, loyalty, inventory)Cloud certifications: AWS Data Analytics, Azure Data Engineer, or GCP Professional Data EngineerBenefitsCompetitive salary + Project Bonuses based on KPIs & Client Satisfaction IndexProfessional growth with global client exposure; clear path to Delivery Manager/Operations ManagerPremium health insurance, annual performance bonuses, certification sponsorship