[Growing EC] Sr. Data Engineer

On behalf of our client—a leading e-commerce and digital retail technology platform in Taiwan—we are seeking an experienced Senior Data Engineer (Lakehouse) to architect, build, and optimize their next-generation enterprise data infrastructure.

What you’ll do

• Lakehouse Architecture & Optimization: Design and implement an enterprise-grade Data Lakehouse infrastructure utilizing compute-storage separation to maximize resource elasticity. Optimize end-to-end ETL/ELT data pipelines and construct robust data models (Kimball, Data Vault, Medallion Architecture) that comply with data governance and support BI and AI/ML applications.

• Real-Time Streaming Systems: Architect, develop, and maintain high-throughput real-time data streaming platforms using Apache Kafka, Apache Flink, and Spark Streaming to power instantaneous internal analytics and operational decisions.

• Hybrid Cloud Infrastructure: Lead the technical integration of hybrid cloud environments (bridging on-premise infrastructure with AWS, GCP, and Azure). Drive containerized deployments using Docker and Kubernetes while leveraging cloud data warehouses (BigQuery, Redshift, Databricks) for cost and performance optimization.

• Cross-Functional Project Leadership: Partner with data scientists, analysts, and business stakeholders to translate complex business needs into scalable data architecture. Lead technical data projects by defining milestones, allocating resources, and ensuring timely, high-quality delivery.

• Data Governance & Tech Innovation: Establish comprehensive data governance policies, metadata management, and lineage tracking in compliance with security standards. Research emerging data frameworks and evaluate the integration of AI-assisted engineering tools and AI/ML data workflows into the platform.

What you’ll bring

• Education & Experience: Bachelor’s degree or higher (Master’s preferred) in Computer Science, Data Science, Information Engineering, or a related field, combined with 5+ years of hands-on data engineering or big data platform development experience, including at least 2+ years designing and managing enterprise-grade data architectures.

• Data Architecture & Modeling: Deep expertise in Data Lake, Data Warehouse, Lakehouse, and compute-storage separation concepts. Proven track record building ETL/ELT workflows using tools like Apache Airflow, Trinity, or Informatica, alongside advanced data modeling techniques (Medallion Architecture, Kimball, Data Vault).

• Programming & AI-Assisted Engineering:

  • Advanced proficiency in Python (writing clean, maintainable code) and SQL (complex querying, execution plan analysis, and performance tuning).

  • Hands-on proficiency with modern AI coding assistants (e.g., GitHub Copilot, Claude Code, Cursor, Codex). Ability to craft effective prompts to accelerate drafting, API integration, and testing while independently validating outputs to maintain strict code quality and security standards.

  • Experience establishing AI-assisted engineering best practices, prompt patterns, and review guidelines across development teams.

• Big Data & Streaming Ecosystem: Strong practical experience with big data frameworks (Apache Spark, Trino), object storage (MinIO, AWS S3, GCS, Apache Ozone), real-time streaming (Kafka, Flink, Spark Streaming), modern data lake formats (Delta Lake, Apache Iceberg, Apache Hudi), and relational database management.

• Cloud & DevOps: Proven experience with cloud platforms (AWS, GCP, Azure), cloud data warehouses (BigQuery, Redshift, Databricks), hybrid cloud design, and container orchestration (Docker, Kubernetes).

• Soft Skills: Excellent problem-solving capabilities, proactive cross-departmental communication skills, and a strong drive for continuous technical innovation.

What sets this company apart

• Massive Data Scale & Impact: Our client is Taiwan's premier digital retail and e-commerce technology powerhouse, offering the chance to architect solutions that process massive daily data volumes and high-concurrency transactions.

• Cutting-Edge Technical Ownership: High autonomy to design modern Lakehouse architectures, implement hybrid-cloud solutions from the ground up, and directly influence enterprise-wide data engineering standards.

• Progressive Engineering Culture: Work in a forward-thinking, agile environment that actively encourages technical experimentation, continuous learning, and the formal integration of modern AI-assisted engineering workflows.

What’s next

If you are a senior data engineer passionate about enterprise Lakehouse architectures, real-time streaming, and solving complex big data challenges at scale, we would love to connect. Please submit your updated English CV to our recruitment team to initiate a confidential discussion regarding this opportunity.