Data Engineer

· Pioneer and implement advanced optimization strategies for large- scale data storage and query systems (big data), focusing on maximizing performance, scalability, and cost- effectiveness.
· Act as a key technical liaison with AI, BI, and DevOps teams, driving the integration of data into complex analytics applications, production- grade machine learning models, and intelligent reporting systems.
· Establish and enforce best practices for data governance, including comprehensive data quality frameworks, centralized metadata management, and automated data lineage processes.
· Collaborate with infrastructure and security teams to architect and operate secure, compliant data systems, ensuring adherence to security protocols, internal regulations, and external standards.
· Lead the design and implementation of the Data Lakehouse architecture on Azure, making critical technology choices across Azure Data Lake Storage Gen2, Delta Lake, Azure Synapse, or Azure Databricks.
· Design, develop, and optimize high- throughput data processing pipelines (ETL/ELT) for a diverse range of sources (on- premise, cloud, streaming, APIs, files, etc.), ensuring resilience and fault tolerance.
· Mentor junior engineers, review code/design specifications, and produce high- quality technical documentation that enables knowledge transfer and efficient operations across product and analytics teams.

Education & Experience
· Minimum of 5 years of hands- on experience as a Data Engineer, with a proven track record of delivering end- to- end data solutions.
· Bachelor’s degree or Master in Information Technology, Data Science, Information Systems, or equivalent.
· Deep, demonstrable expertise in implementing and operating data infrastructure on Azure Cloud, with high proficiency in:
Architecture and implementation using Azure Synapse Analytics, Azure Data Factory, or Azure Databricks.
Azure Data Lake Storage Gen2
Real- time/Streaming technologies like Azure Event Hub, Azure Stream Analytics, or Apache Kafka.
· Extensive experience designing and working with advanced data models (e.g., Star Schema, Snowflake Schema, Mastery of Lakehouse Architecture and Delta Lake best practices).
· Expert proficiency in SQL and a programming language such as Python or PySpark, along with a strong theoretical and practical understanding of distributed computing principles.
· Required experience in designing and managing large- scale production data systems, implementing robust real- time pipelines, and integrating data directly into AI/ML model serving layers.
Soft Skills
· Logical thinking, strong analytical, and problem- solving skills.
· Strong collaboration skills with other technical teams (AI, DevOps, Product, ...).
· Openness to learning new technologies, adapting to change, and experimenting
· Ability to work independently, proactively, and with a systematic mindset.

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Cập nhật gần nhất lúc: 2026-01-12 07:25:03