Platform Engineering LeadSenior Associate Director, Data and Analytics Specialist

Some careers shine brighter than others.

If youre looking for a career that will help you stand out join HSBC and fulfil your potential. Whether you want a career that could take you to the top or simply take you in an exciting new direction HSBC offers opportunities support and rewards that will take you further.

HSBC is one of the largest banking and financial services organisations in the world with operations in 64 countries and territories. We aim to be where the growth is enabling businesses to thrive and economies to prosper and ultimately helping people to fulfil their hopes and realise their ambitions.

We are currently seeking an experienced professional to join our team in the role of Senior Associate Director Data and Analytics Specialist

In this role you will:

• Define the platform vision roadmap principles and standards for Tier1 data services and establish and enforce federated governance across entitlement privacy retention lineage catalog quality integrity and usage monitoring.
• Define KPIs and operational measures (e.g. data freshness quality scores consumption latency unit cost) and drive continuous improvement.
• Architect and evolve a scalable secure resilient and costoptimised GCP data platform using services including: BigQuery Dataflow Pub/Sub GKE Cloud Storage Bigtable Composer/Airflow IAM Logging/Monitoring and Artifact Registry.
• Lead build-out of the Control Plane and unified portal (iHUB) enabling selfservice consumption and consistent multitenant patterns oversee data modelling and trusted source curation including reference/master data strategy.
• Drive observability and reliability (metrics tracing anomaly detection alerting) including AIassisted data issue identification/repair where appropriate.
• Own and mature CI/CD standards for data platform services and pipelines (e.g. GitLab CI/Jenkins) including automated testing security scanning and gated releases implement Infrastructure as Code (Terraform) and GitOps-style operating practices for repeatable auditable environment provisioning embed security by design across the DevOps toolchain (IAM KMS secrets management policy-as-code vulnerability management).
• Define and establish SRE-aligned practices: SLO/SLI definition error budgets incident management root-cause analysis problem management and reliability engineering and strengthen operational controls: release governance change management readiness resilience/DR testing runbooks and on-call support patterns.
• Hands-on experience with agentic AI patterns (e.g. tool-using agents plannerexecutor loops retrieval-augmented generation (RAG) function/tool calling and multi-agent collaboration) applied to engineering or data operations use cases (e.g. data quality triage lineage inference incident support automated remediation).
• Exhibit experience applying FinOps practices to large-scale cloud data platforms balancing cost performance reliability and risk in a regulated capability in cost modelling and unit economics for data platforms (e.g. cost per TB processed cost per query/job cost per pipeline run cost per domain/tenant) with clear chargeback/showback approaches where applicable.
• Establish capability in cost modelling and unit economics for data platforms (e.g. cost per TB processed cost per query/job cost per pipeline run cost per domain/tenant) with clear chargeback/showback approaches where applicable.

To be successful you will:

• 15 years data/platform engineering; 5 years leading cloud data programs.
• Proven largescale GCP data architecture delivery.
• Strong SQL Python Terraform streaming governance implementation.
• Track record in building selfservice and multitenant data platforms.
• Banking decisioning integration exposure (e.g. CDH/decisioning uplift) and/or CDMS integration.
• Practical experience delivering AI-enabled data platforms on cloud including governed integration of GenAI/ML workloads with enterprise data services (catalogue lineage access controls retention).
• Experience building and tracking FinOps KPIs and reporting (e.g. budget adherence forecast accuracy savings delivered unit-cost trends) and driving continuous improvement with engineering teams
• Strong understanding of AI governance and controls in a regulated environment: model risk considerations prompt/tooling guardrails data leakage prevention policy-based access logging monitoring evaluation and human-in-the-loop approval where required.

Youll achieve more when you join HSBC.

is an equal opportunity employer committed to building a culture where all employees are valued respected and opinions count. We take pride in providing a workplace that fosters continuous professional development flexible working and opportunities to grow within an inclusive and diverse environment. We encourage applications from all suitably qualified persons irrespective of but not limited to their gender or genetic information sexual orientation ethnicity religion social status medical care leave requirements political affiliation people with disabilities color national origin veteran status etc. We consider all applications based on merit and suitability to the role.

Personal data held by the Bank relating to employment applications will be used in accordance with our Privacy Statement which is available on our website.

Issued by HSBC Software Development India