AI-Data and Analytics Lead(Python, SQL, LLM, Cloud)/Associate Director
HSBC Global Services Limited Pune, Maharashtra, India
Financial Services · 10,001+ employees
About the role
The role involves owning the serving layer for Enterprise Finance value stream MI and conversational analytics while leading end-to-end data modeling. You will also partner with data engineering to build pipelines and implement fine-grained security for Finance-controlled data.
What they look for
Requirements
Candidates must have deep hands-on experience designing analytics serving layers on cloud warehouses and strong expertise in dimensional modeling. Proficiency in SQL, Python, and AI analytics patterns like LLM/RAG is essential for this position.
Benefits
Full description
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 Associate Director, Data and Analytics
In this role, you will:
- Own the serving layer for Enterprise Finance value stream MI and conversational analytics initiative , defining curated datasets/views/APIs with clear SLAs/SLOs, performance and cost targets.
- Lead the end-to-end data model across TM1-sourced actuals/forecasts/FRP cycles, optimized for analytics consumption and scalable serving patterns.
- Partner and deliver the department-wide semantic layer to standardize key Finance metrics, dimensions and calculation logic for consistent MI and AI outputs.
- Partner with data engineering to build and operate TM1 → GCP pipelines (scheduled + near real-time), including orchestration, reconciliation, monitoring and runbooks.
- Shape Finance MI capabilities by applying FP&A expertise to define trusted KPI packs (e.g., actuals vs forecast/plan, variance drivers, trending) and consistent scenario/version handling.
- Implement fine-grained security and entitlements in the serving layer (row/column security, hierarchy-based access, auditing) suitable for Finance-controlled data.
- Enable text-to-query capabilities by defining governed query contracts (semantic-to-physical mappings, schema validation, caching, safe fallbacks) grounded in curated datasets.
- Support AI/RAG readiness by curating Finance artefacts (definitions, dimensional context, report examples), and partnering on evaluation to ensure accuracy, explainability and trust.
To be successful in this role, you should meet the following requirements:
- Deep, hands-on experience designing analytics serving layers on cloud warehouses (preferably BigQuery): curated/serving datasets, performant views/materialisations, partitioning/clustering, cost optimisation and workload management.
- Strong expertise in dimensional modelling and analytical data design: star/snowflake schemas, conformed dimensions, SCD patterns, hierarchies, time/scenario/version modelling, and non-/semi-additive measures.
- Proven experience building a metrics/semantic layer using modern approaches (e.g., dbt models/metrics, LookML-style modelling, Cube/MetricFlow-like patterns or equivalent), including metric versioning, validation rules and lineage/metadata management.
- Solid data engineering capability for batch and near real-time pipelines: orchestration (e.g., Airflow/Composer), CDC/event patterns where relevant, data quality frameworks (tests/reconciliation), monitoring/alerting and operational readiness.
- Strong SQL + optimisation skills across complex analytical queries: window functions, incremental processing, aggregation strategies, caching patterns, and query plan/performance troubleshooting.
- Working proficiency in Python for data/analytics engineering, automation, validations, and integration tooling.
- Practical experience with AI analytics patterns: LLM/RAG fundamentals, embeddings/vector search, deterministic text-to-SQL/DSL grounding against governed schemas, and evaluation techniques (golden sets, retrieval quality, regression tests).
- Strong platform/security engineering awareness: fine-grained access controls (RBAC/ABAC, row/column security, hierarchy-based entitlements), secrets management, audit logging, and secure-by-design patterns for sensitive Finance data—grounded in FP&A reporting needs and controls.
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
Similar roles
-
Robotic Python Operator
Columbia Industries, LLC Starkville, Mississippi, United States
-
Python Data Analyst (Fraud and Risk)
bet365 Denver, Colorado, United States · $65K–$75K/yr
-
Intermediate/Senior Software Engineer (Python) Career Opportunities at Dev.Pro
Dev.Pro Chișinău, Moldova
-
Senior Python Data Engineer
Miratech India
-
Python Senior Developer
Paradigma Digital - Nuestras ofertas de Empleo Pozuelo de Alarcón, Community of Madrid, Spain
-
Middle/Senior Forward Deployed Engineer (Python, AI)
Exadel Canada · CA$135K–CA$270K/yr