Senior Data Platform & Software Engineering Principal - Vice President 2

VP2 - Data Platform – Capability Engineer

State Street Investment Management's Data, Analytics & AI Services (DAAIS) team is seeking a Senior Data Platform & Software Engineering Principal (Vice President -2) for our Bangalore, India office. This leadership role is accountable for the architecture, delivery, and operational excellence of modern data platform and software capabilities that power the investment management business. The role partners with global teams and stakeholders across regions and time zones to align priorities and execute consistently. The successful candidate brings deep hands-on expertise in large-scale data platform architecture, distributed computing, data pipeline engineering, and modern cloud architecture, and will hire, build, and mentor a high-performing engineering team.

Key Responsibilities

• Define the vision, target architecture, and roadmap for a unified cloud-native data platform (ingestion, transformation, storage, governance, secure access).
• Build and evolve shared platform capabilities for data ingestion, transformation, governance, job orchestration, and metadata management with reliability, scalability, and operability.
• Design and optimize Apache Iceberg tables (partitioning, compaction, metadata) for consistent performance across compute engines.
• Establish engineering standards for CI/CD, IaC (Terraform/CloudFormation), automated testing, schema/versioning, data quality, and observability.
• Partner with Product, Analytics, ML, and SMEs across regions and time zones to define data semantics and data product contracts (schemas, SLAs, docs, versioning) and enforce governance and compliance.
• Build curated semantic models (marts/serving models) and publish governed BI endpoints and/or consumption APIs.
• Optimize pipeline and query performance using partitioning/clustering, caching, archiving, and lifecycle management (retention/purge).
• Own platform operations, including on-call and incident response, backfills, post-incident reviews, and reliability improvements.
• Build and lead a scaled engineering organization across multiple squads/pods; hire and develop tech leadership to deliver with engineering and operational excellence.
• Manage outsourcing partners by overseeing SOWs, tracking capacity, and ensuring delivery against milestones.

Required Qualifications

• 17+ years in software/data engineering, including technical leadership for large-scale data platforms; BS/MS in Computer Science/Engineering (or equivalent experience).
• Demonstrate strong communication and stakeholder management; influence architecture decisions across engineering, product, security, and enterprise architecture.
• Demonstrate experience leading a multi-team engineering organization with end-to-end accountability for delivery, quality, and operations.
• Write production-grade Python and SQL (Java/Scala a plus); design, debug, and optimize distributed data processing.
• Tune and troubleshoot Spark (batch and streaming), including performance and cost optimization.
• Build and operate lakehouse platforms using Snowflake and Databricks on AWS (GCP or Azure acceptable) for high-concurrency analytics.

Preferred Qualifications

• Bring prior data platform engineering experience in a financial institution (asset management preferred).
• Work with structured and alternative/unstructured data sources and their processing patterns (batch, streaming, and event-driven).
• Leverage AI-assisted coding tools (e.g., GitHub Copilot, Claude Code) to improve developer productivity while maintaining code quality.