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Renova Cloud is a leading provider of Cloud Computing, DevOps, and AI Solutions in Vietnam. As the AWS Partner of the Year for 2023, 2024 and 2026, we bring together a highly skilled team of cloud architects, AI/data engineers, and DevOps professionals. We specialize in helping enterprises modernize their workloads, accelerate cloud adoption, and embrace the next generation of AI and automation technologies.
In July 2025, Renova Cloud signed a Strategic Collaboration Agreement (SCA) with AWS (Amazon Web Services) to accelerate the adoption of Generative AI in Vietnam. Following this, we officially launched the Renova AI Factory — a dedicated innovation hub in Ho Chi Minh City designed to incubate and scale GenAI workloads, enabling enterprises to co-create real-world solutions with our experts.
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Position Summary
Design, build, and maintain data pipelines and cloud architectures (Data Lakes/Warehouses), prepare datasets for analytics and AI/ML, and ensure high performance, reliability, and data quality across cloud environments.
Key Relationships
- Design, develop, and test software modules and applications for efficient data collection and processing.
- Identify, create, and prepare datasets required for modern data analytics and machine learning use cases.
- Build and implement modern data architectures (Data Lake, Data Warehouse, and Data Lakehouse) using cloud-native services.
- Develop, execute, and document test cases to ensure data quality, accuracy, and compliance with requirements.
- Deploy data solutions to cloud platforms and integrate them with other application components and services.
- Monitor, maintain, and optimize data applications to ensure performance, scalability, and reliability.
- Support additional tasks and initiatives that contribute to the success of the team and align with the company’s mission and goals.
Key Relationships
Internal
Team members
External
Clients
Partners
Qualifications and Experience
Memberships
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Fluency in SQL and Python is mandatory (Scala or Java knowledge is a plus).
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Hands-on experience with cloud data processing services (AWS, Azure, or GCP).
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Familiarity with ETL/data integration tools (AWS Glue, Fivetran, Talend, Airbyte).
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Experience with orchestration platforms (Apache Airflow, Dagster, Luigi).
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Working knowledge of real-time processing frameworks (Kafka, Apache Flink, Apache Beam).
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Interest or exposure to Big Data technologies (Databricks, Snowflake, Apache Spark, Hadoop).
Experience
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2–3 years of hands-on experience in data engineering and cloud-native data platforms.
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Proven track record of developing, testing, and deploying ETL/ELT pipelines and data lake/warehouse architectures.
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Demonstrated history of implementing data quality tests, dataset preparation for ML/analytics, and system performance monitoring.
Personal Requirements
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Collaborative team player capable of working under the direction of the Lead Data Engineer.
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Detail-oriented approach to code quality, data accuracy, testing, and documentation.
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Proactive learner driven to stay updated on emerging cloud, AI, and Big Data technologies.
