NewEra Inc. is an AI-first technology company specializing in digital transformation solutions for retail and enterprise partners. This role owns the engineering work behind NewEra's data foundation. You will design, build, and operate the pipelines, models, and platform integrations that turn raw data into reliable assets for product, analytics, and AI use cases. The goal is not simply to move data from one system to another — it is to make data dependable enough that teams can use it to make decisions and ship products with confidence.
Mô tả công việc
- Design, build, and maintain robust batch and streaming data pipelines across product, operational, and third-party data sources
- Develop scalable ingestion, transformation, orchestration, and data-serving patterns that meet business and technical requirements
- Choose appropriate storage and processing technologies based on data volume, latency, reliability, security, and cost
- Build reusable data components and conventions to reduce duplicated work across teams
- Document critical data flows, dependencies, ownership, and operational assumptions
- Design and maintain well-structured data models for analytics, reporting, product features, and AI applications
- Define data contracts, schema-change practices, validation checks, and quality thresholds with upstream and downstream teams
- Investigate data discrepancies at source and fix root causes rather than relying on downstream workarounds
- Make lineage, freshness, completeness, and known limitations visible to data consumers
- Partner with analysts, product teams, and AI engineers to ensure datasets reflect the correct business meaning and context
- Own the reliability of assigned pipelines, including monitoring, alerting, recovery, and incident follow-up
- Measure and improve pipeline freshness, failure rates, processing latency, and compute/storage costs
- Establish appropriate testing, deployment, versioning, and rollback practices for data workflows
- Plan for schema evolution, backfills, replay, and recovery from upstream outages
- Implement access controls, data minimisation, retention practices, and secure handling of sensitive information
- Work with application engineers, platform engineers, analysts, and AI teams to make data assets fit for use
- Participate in design reviews and provide clear guidance on data architecture and engineering trade-offs
- Maintain practical documentation and support onboarding for data consumers
Yêu cầu
- 5+ years of hands-on experience in data engineering, backend/data platform engineering, or a closely related field
- Strong SQL and proficiency in Python or another production-grade data engineering language
- Experience building and operating production ETL/ELT pipelines and data transformation workflows
- Practical knowledge of data modelling, warehouse/lakehouse concepts, orchestration, and distributed data processing
- Experience with data quality checks, automated testing, monitoring, and production incident resolution
- Sound understanding of cloud infrastructure, APIs, Git, CI/CD, and engineering best practices
- Working proficiency in English for technical documentation and collaboration
Ưu tiên
- Experience with tools such as Airflow or Dagster, dbt, Spark, Kafka, and modern cloud data warehouses or lakehouses
- Experience with streaming/event-driven architectures and data contracts
- Experience preparing datasets for machine learning, LLM applications, or RAG systems
- Experience with data governance, lineage, privacy, and access-control implementation
- Experience in fintech, payments, or other data-sensitive technology environments
Quyền lợi
- Competitive salary commensurate with experience
- Performance-based bonus
- Full statutory insurance coverage (BHXH, BHYT, BHTN) per Vietnamese labor law
- Direct ownership of critical data infrastructure supporting AI and product teams
- Clear career growth path in Data Engineering / Data Platform