Consultant Specialist

Lead cloud data product development: define product boundaries, data contracts, SLAs/SLOs, and consumption patterns for Finance/Risk users and downstream systems. Design and build cloud data products (curated datasets/semantic layers/marts as applicable) using strong modelling practices and reusable engineering patterns. Be hands-on: develop, review and maintain production-grade code using advanced SQL and Python; mentor engineers/analysts. Establish strong data quality and control framework: profiling, rules, exception handling, reconciliation, and “source-to-target” validation with traceable evidence. Apply cloud data architecture principles: security-by-design (IAM, encryption, secrets), non-functional requirements, observability/monitoring, and operational readiness. Collaborate with other data teams (Business, Finance, Risk and Technology) on data governance, metadata/lineage, data standards and stewardship, and product adoption—ensuring data products are discoverable, trusted, and consistently used across the bank. Support production operations: monitoring/alerting, incident/problem management, root-cause analysis, and continuous improvement of reliability. Degree holder (or equivalent experience). 3+ years' experience delivering data projects (data engineering / data product development), including building and deploying cloud-based data pipelines and curated datasets for enterprise use. Proven Technical Lead experience delivering cloud-based data products or data engineering solutions (design authority + hands-on build). Strong hands-on skills: advanced SQL plus Python (basic working proficiency) for transformations, validations and automation. Familiarity with cloud data architecture: data modelling, integration patterns, security, scalability, resilience, and cost/performance optimisation. Solid understanding of SDLC and technology delivery practices (e.g., version control, code review, environment management). Experience implementing data governance and controls (lineage, auditability, approvals/evidence) in a regulated environment. Finance and Risk domain knowledge is required; experience delivering data solutions for Finance and/or Risk functions. Fluent spoken Cantonese; strong written English for technical documentation and stakeholder communications. Strong risk and control mindset; able to maintain audit-ready artefacts. Cloud/data engineering/architecture certifications (Azure/AWS/GCP). Experience with data observability/DQ tooling, metadata/lineage tooling Exposure to regulatory programmes, data remediation, Finance/Risk reporting, or End User Computing remediation.