Principal Engineer – Data Platforms, Azure & GenAI
London Stock Exchange Group2 days ago
Bengaluru, IndiaStaff+
Responsibilities
- Architect, design, and implement engineering deliverables across complex, high-scale data landscapes.
- Design, build, and optimize batch and streaming data pipelines across on-premises and Azure environments.
- Own data modeling and engineering strategy for analytics, including data quality, discoverability, trustworthiness, observability, and pipeline reliability.
- Design and build microservices and backend APIs using appropriate compute models and scalable system-design patterns.
- Apply resilient, event-driven, asynchronous, and maintainable architecture patterns.
- Champion CI/CD and DevOps practices across on-premises and Azure environments.
- Write production code, review designs, and solve the team’s most difficult technical problems.
- Partner with senior leaders and cross-functional stakeholders to translate business priorities into scalable technical solutions.
- Evangelize and drive adoption of Generative AI and Agentic AI across engineering teams.
- Mentor and coach engineers at all levels and elevate engineering standards across the organization.
- Drive innovation, experimentation, continuous improvement, proof-of-concepts, hackathons, and engineering culture initiatives.
Requirements
- 15+ years of progressive experience in data and software engineering with ownership of large, complex data landscapes.
- Deep expertise in data engineering, including batch and streaming pipelines, ETL/ELT, data modeling, and warehousing for large-scale analytics.
- Strong database and data-management expertise, including advanced SQL and relational or analytical data modeling.
- Strong proficiency in at least one programming language, with Python or Java preferred, and a record of delivering production-grade code.
- Proven experience designing and building microservices architectures, system designs, and CI/CD practices.
- Hands-on experience with at least one major cloud platform, preferably Azure.
- Experience driving adoption of Generative AI and Agentic AI capabilities within an engineering organization.
- Exposure to modern GenAI and LLM tooling such as Azure OpenAI, Copilot-style agents, RAG pipelines, prompt engineering, and AI-assisted development workflows.
- Financial services or banking experience and familiarity with domain-specific data and compliance considerations are preferred.
- Experience influencing senior leadership and executive stakeholders on technical strategy is preferred.
- Demonstrated mentorship and technical coaching experience is preferred.
- A track record of innovation initiatives such as proof-of-concepts, hackathons, or engineering culture transformation is preferred.
Benefits
- Competitive compensation package, comprehensive benefits, and ongoing career-growth and skill-development investment.
- Hybrid, digital-first work arrangement requiring at least one office day per week, with flexibility to discuss work arrangements.
- Healthcare, retirement planning, paid volunteering days, and wellbeing initiatives.
- Opportunities for continuous learning and professional development.
- High-impact projects involving AI products, extensive datasets, modeling, and analytics solutions.
About London Stock Exchange Group
London Stock Exchange Group (LSEG) provides market infrastructure, financial data, and analytics to banks, asset managers, and corporations. Its businesses span capital markets (London Stock Exchange), post-trade clearing (LCH), and information services including FTSE Russell indices and the Refinitiv data platform, funded by transaction fees, subscriptions, and licensing. Headquartered in London and publicly listed on the LSE, the group serves global customers seeking trading, clearing, benchmarks, and enterprise data solutions.