Associate Director, Data and Analytics
HSBC View all jobs
- Guangzhou, Guangdong
- Permanent
- Full-time
- Architect, build, and optimize data pipelines for batch, streaming, and event-driven data workflows using GCP services such as BigQuery, Dataflow, Pub/Sub, Cloud Storage, and Cloud Composer.
- Develop and maintain ETL/ELT frameworks that transform data from multiple sources into structured, query-ready formats.
- Work with structured, semi-structured, and unstructured data across diverse sources including APIs, files, logs, and databases.
- Implement data quality, lineage, and monitoring systems using Cloud Monitoring and alerting according to latest group strategies.
- Collaborate with Data Scientists, Analysts, and Product Managers to deliver scalable datasets supporting analytics and reporting.
- Ensure data security, governance, and compliance through IAM roles, VPC configurations, and best-in-class encryption practices.
- Contribute to architecture decisions that balance scalability, performance, and cost within GCP.
- Mentor junior engineers, enforce best practices in data engineering, and lead code review sessions.
- Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
- 5+ years of professional experience designing and operating data pipelines and platforms.
- Strong proficiency in SQL and Python for data processing and automation.
- Deep hands-on experience with GCP services (BigQuery, Dataflow, Cloud Storage, Pub/Sub, Dataproc)
- Experience in use of AI assist tooling for coding, test management.
- Experience managing data lake or warehouse infrastructure, integrating both structured and unstructured sources.
- Strong understanding of data modeling, partitioning, and schema design for analytical workloads.
- Excellent problem-solving and analytical thinking.
- Effective communication across technical and business teams.
- Leadership mindset with mentoring and cross-functional collaboration experience.
- Proven ability to manage and coordinate across multiple domains
- Familiarity with industry best practices for engineering maturity, standards, and infrastructure components.
- Experience as data engineering lead in large-scale projects, integrating ML pipelines or AI workflows on multiple cloud platforms.
- Certification: Google Cloud Professional Data Engineer or relevant Data Engineering or AI Certifications (preferred).