Data Engineer (AWS Glue/Athena, SQL & Analytics) - Mid/Senior
Full-time — Danang — Agreement
Middle/Senior — Production
We are looking for a hands-on Data Engineer (Mid–Senior) with strong English communication to build and operate reliable, scalable data pipelines and analytics-ready datasets on AWS.
We are looking for a hands-on Data Engineer (Mid/Senior) with strong English communication to build and operate reliable, scalable data pipelines and analytics-ready datasets on AWS.
In this individual contributor role, you will design and maintain ETL/ELT workflows (AWS Glue, Athena), optimize SQL and databases for performance, and collaborate closely with engineering, product, and analytics stakeholders to enable trustworthy data-driven decisions.
Job duties and responsibilities
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Design, build, and maintain scalable, robust, and maintainable data pipelines on AWS, from ingestion to curated datasets for analytics and downstream services.
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Develop and operate production ETL/ELT workflows using AWS Glue (Spark/Python) and query/serving layers using Amazon Athena; integrate with S3 and other AWS data services as needed.
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Diagnose and resolve data issues (job failures, pipeline breakdowns, schema drift, and unexpected row-level changes), production outages, and performance bottlenecks to maintain system reliability.
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Write high-quality SQL and perform SQL tuning (partitioning strategy, file formats, query optimization) to improve efficiency, cost, and scalability across data stores and warehouses/lakes.
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Own data quality and observability: implement validation checks, lineage/metadata practices, monitoring/alerting, and root-cause analysis to ensure trustworthy datasets.
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Facilitate secure and efficient data access for analytics (e.g., Athena permissions, data sharing patterns), balancing liberalization with compliance and privacy requirements; provide on-call/incident support as needed to meet SLAs.
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Work with the Data Lead and engAineering team to implement optimal ingestion, storage, and transformation strategies; stay ahead of industry trends and recommend best-in-class data engineering technologies and practices.
Requirements
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Minimum 4+ years of relevant experience in Data Engineering (Mid–Senior level).
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Strong English communication skills (written and spoken) for collaborating with international stakeholders.
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Strong proficiency in Python; hands-on experience using Pandas for data manipulation, transformation, and analysis of large datasets.
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Strong SQL skills with proven experience in performance tuning and query optimization (Athena and relational databases).
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Hands-on experience building, deploying, and debugging ETL/ELT workflows in production on AWS (AWS Glue, Athena; plus S3, IAM, CloudWatch).
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Solid database knowledge (data modeling, transactional vs. analytical workloads, indexing, constraints, and data consistency concepts).
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Strong problem-solving skills, especially in navigating ambiguous and unknown data issues and performing root-cause analysis.
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Ability to partner effectively with engineering, product, and data analytics teams to deliver business-ready datasets.
Nice to have:
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Experience with modern data lake/lakehouse patterns (S3 + Glue Data Catalog), partitioning, and file formats (Parquet/ORC)
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Experience with data orchestration and automation (e.g., Airflow/Managed Workflows, Step Functions) and CI/CD for data pipelines
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Familiarity with BI/analytics tools and data modeling concepts (dimensional modeling, metrics definitions) to support Data Analytics use cases
Benefits and perks
Compensation & Bonuses
- Competitive salary package with attractive bonuses
- Up to 100% salary during probation period
- Holiday bonuses throughout the year
- 13th-month salary & performance bonus based on business results and individual performance
Working Environment
- 5 working days/week (Monday to Friday)
- Flexible remote working policy
- Free pantry & daily snacks
In-house gym facilities
- Comfortable nap/rest areas
- Employee discounts at Enouvo Cafe in the same building.
Healthcare & Insurance
- PVI Healthcare insurance for employees
- Family healthcare support under company policy
- Full social, health, and unemployment insurance coverage
- Annual health check-up
Leave & Work-life Balance
- 12 paid annual leave days
- Leave carry-over policy
- Special sick leave support
- Social insurance leave benefits in accordance with regulations
- Additional leave days based on seniority
- Paid marriage and bereavement leave
Company Culture & Internal Activities
- Wedding, newborn, and birthday gifts
- Employee wellness and hospital visit support
- Internal Activities (Annual Company Trip, Year-End Party, celebration events,..)
- Project & functional team building activities
- Sport clubs: football, badminton, and more
Learning & Development
- Udemy Business account, Elsa Premium account for English learning
- Weekly internal knowledge-sharing sessions
- Opportunities to become a mentor for interns and students
- Professional certification rewards
- Participation in Hackathons & innovation, AI activities,..
How to Apply
Does this role sound like a good fit? Email us at [email protected]
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