Some careers shine brighter than others.
If you’re 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 Sr. Associate Director, Software Engineering Specialist
In this role, you will:
Technical leadership & architecture
- Solution architecture and modernisation: Own the solution architecture for high-performance data pipelines and microservices, covering non-functional requirements such as resilience, scalability, latency, observability, and security. Define and drive modernisation roadmaps, including re-platforming, refactoring, and microservices decomposition, while minimising disruption to live services.
- Engineering standards and technical debt: Establish standards for API design, event-driven integration, data modelling, testing, CI/CD, and operational readiness. Manage technical debt through clear prioritisation, measurable outcomes, and continuous improvement.
- Application and data platform engineering: Architect, design, and build core services using Java 8+, Spring Boot 3, relational databases, cloud storage such as Amazon S3 and Google Cloud Storage, serverless technologies such as AWS Glue, Glue Data Catalog, Lake Formation, Amazon EKS, Step Functions, SQS, and event-streaming patterns. Lead the design and implementation of solutions using Apache Spark, YuniKorn, and/or Apache Beam where appropriate.
- Cloud engineering — GCP: Drive engineering delivery on Google Cloud Platform, using Dataflow, Pub/Sub, Google Cloud Storage, Composer/Airflow, BigQuery and/or ClickHouse, and Google Kubernetes Engine. Ensure data quality, integrity, lineage, and security controls across pipelines and downstream consumption.
- Operational excellence: Own production reliability through monitoring, alerting, capacity planning, performance tuning, incident resolution, resilience improvements, and cost optimisation.
- AI-enabled engineering productivity: Use AI tooling and at least two code-development large language models (LLMs) to support regular engineering tasks, agentic workflows, and specification-driven development. Build AI-enabled automation for scripting, tooling, and unit, regression, and functional testing, using Python where appropriate.
- Technical collaboration: Partner with engineers through code reviews, pair debugging, performance tuning, and production incident resolution.
- People leadership and stakeholder management: Coach and mentor engineers at different levels, fostering a culture of craftsmanship, accountability, and continuous improvement. Communicate effectively with senior stakeholders by translating business outcomes into technical plans and delivery milestones. Proactively manage risks, dependencies, and delivery impediments, with clear mitigation and escalation paths.
To be successful in this role, you should meet the following requirements: (MAX 8 Points)
- Cloud, Kubernetes and deployment tooling: Google Kubernetes Engine (GKE), Docker, OpenShift, Kubernetes, CI/CD pipelines, and GitLab CI/CD.
- Observability: Prometheus, Grafana, Stackdriver/Cloud Monitoring, and distributed tracing.
- Cloud and Kubernetes security: Automated secrets management, Identity and Access Management (IAM), network segmentation, and secure software development lifecycle (SDLC) practices.
- Data engineering and processing: Apache Spark, with proficiency in at least one Spark-related language, preferably Python or Spark SQL.
- Advanced SQL and data management: Data modelling, cloud storage mechanisms, and file formats such as Parquet and Iceberg.
- Databases and build tooling: DocumentDB and SBT.
- Containerised application development: Hands-on experience designing and developing containerised applications, including auto-scaling and load balancing.
- DevOps delivery: Experience developing end-to-end DevOps pipelines for automated testing, regression testing, and deployments. Experience with Jira and Confluence is required.
- AI tooling: Hands-on experience with AI tooling, preferably including Model Context Protocol (MCP) integration. Familiarity with Claude Code, SpecKit, specification-driven development (SDD), and AI/LLM technologies is desirable.
- Front-end technologies: React and TypeScript exposure is helpful but not essential.
- Cloud technology: Hands-on experience with cloud technologies and a strong technical background.
- Financial services domain knowledge: Understanding of Financial Accounting, Credit Risk, Market Risk, Operational Risk, and Regulatory Reporting.
You’ll achieve more when you join HSBC.
www.hsbc.com/careers
HSBC is 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. 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