Sr. Principal Software Engineer

Job highlights

• Formal training or certification on software engineering concepts and 10+ years applied experience . Software engineering experience with significant time architecting large-scale data platforms.
• Drive lineage and auditability: every query and every distributed dataset must be traceable,correlated,and reproducible for regulatory and internal audit needs.

We re looking for a tech leader ready to focus on Data governance, authorization, and data-mesh architecture - with regional technical leadership across the India team

As a Senior Principal Software Engineer at JPMorgan Chase within the Commercial & Investment Banks Markets - Markets Data Lake (MDL) team, you will be the technical authority for how data is governed, secured, and authorized across this mesh, and you will provide regional technical leadership across the India team - one of MDLs primary engineering hubs. You will set direction, grow senior talent locally, and act as the senior technical anchor in-region, while staying hands-on with the platforms most critical governance and authorization components.

Job responsibilities

• Serve as the senior technical leader in-region for the India-based MDL engineering team, setting technical direction and ensuring alignment with the global platform roadmap. Grow and mentor senior, staff, and up-and-coming engineers in India; establish a strong local engineering culture, review practices, and career-development pathways.
• Own regional delivery of major platform initiatives end-to-end, coordinating across time zones with global stakeholders and partner teams. Build in-region depth in governance, authorization, and data-mesh capabilities so the India team owns critical platform domains, not just execution.
• Represent MDL locally - interviewing and hiring, onboarding, and raising the engineering bar across the India hub. Bridge global and regional priorities, ensuring the India teams work is visible, influential, and tightly integrated with the broader organization.
• Architect the data-mesh platform: define what a “data product” is on MDL - its contracts, SLAs, schemas, ownership, lifecycle, and interoperability standards - and build the self-serve platform capabilities domain teams use to publish them. Establish federated computational governance: design the policies-as-code framework that lets central standards (security, quality, entitlements, retention) be enforced automatically across independently-owned domains.
• Build the data-product substrate: catalog, discovery, lineage, versioning, and distribution across the platforms query engines, so consumers can find and query products through the semantic layer and NL-query interfaces without bypassing controls.
• Keep the architecture engine-agnostic - design governance, entitlements, and data-product contracts to work uniformly across current and future storage and compute engines rather than being tied to any single technology. give domains freedom to model and evolve their products while guaranteeing platform-wide consistency and safety.
• Own the governance model end-to-end: data classification, metadata management, lineage, data quality, retention, and audit across every MDL data product. Codify governance as code - schema/contract validation, quality gates, and policy checks embedded in publishing and CI/CD pipelines so governance is enforced, not advisory. Drive lineage and auditability: every query and every distributed dataset must be traceable, correlated, and reproducible for regulatory and internal audit needs.
• Partner with data owners, risk, compliance, and privacy to translate regulatory and firm obligations into automated platform controls. Own the authorization architecture for MDL: fine-grained, row- and column-level entitlements enforced consistently across every query engine and the query/agent layer (nl_query/execute_query).
• Design a scalable entitlements model - attribute/role/policy-based access control, entitlement propagation from source systems, and least-privilege by default. Guarantee “no query bypasses entitlements”: ensure NL-generated and raw SQL alike are planned and executed within the callers entitlement scope, with credentials brokered securely.
• Harden identity and access: integration with enterprise IdP/OAuth2, token lifecycle, secrets handling, and full access audit trails. Set technical direction across …