Level

State Street

Data Platform - Capability Engineer - Assistant Vice President

AI in this role

Senior Data Engineering Lead building and operating modern data platforms and AI-ready data capabilities for investment management.

claudecopilotdatabricksclaude-codeapache-sparksnowflakeapache-iceberg
data-engineeringcloud-architecturedata-governancedistributed-computing

Role Summary

State Street Investment Management’s Data, Analytics & AI Services (DAAIS) team is seeking a Senior Data Engineering Lead (Assistant Vice President –2) for our Bangalore, India office. This role is accountable for the design, build, and operate of modern data platform and software capabilities that enable investment management business. The successful candidate will bring deep hands-on expertise in large-scale data platform architecture, distributed computing, data pipeline engineering, and modern cloud architecture. This role will execute on the broader platform roadmap in partnership with senior leadership and global stakeholders and may lead a small team/pod to deliver reliable, scalable platform outcomes.

 Key Responsibilities

  • Design, build, and operate modern data platform capabilities across lakehouse, batch, streaming, metadata/catalog, observability, security, and governed consumption layers.
  • Develop scalable batch and streaming data pipelines using Apache Spark, Snowflake, and/or Databricks, applying strong engineering practices for performance, reliability, reusability, and cost efficiency.
  • Implement and optimize Apache Iceberg tables and open data formats, including partitioning, compaction, metadata management, and cross-engine performance tuning.
  • Apply disciplined software and data engineering practices across CI/CD, Infrastructure as Code, automated testing, schema/version management, data quality controls, and end-to-end observability.
  • Partner with Product, Analytics, ML, and business SMEs to define data semantics, data product contracts, schemas, SLAs, documentation, access controls, and governed serving models.
  • Engineer data governance capabilities across lineage, observability, permissions, entitlement enforcement, sensitive data classification, masking/tokenization, auditability, and policy-based controls.
  • Create AI-ready data assets by enforcing standards for completeness, accuracy, validity, consistency, timeliness, uniqueness, lineage, provenance, metadata quality, and semantic consistency.
  • Optimize platform performance and cost through workload tuning, partitioning/clustering, caching, lifecycle management, retention/purge strategies, and query optimization.
  • Own operational stability by troubleshooting production issues, supporting backfills, participating in incident response, driving root-cause fixes, and improving platform reliability.
  • Provide technical leadership for a small team or pod, including planning, mentoring, delivery oversight, engineering standards, and operational excellence.

Required Qualifications

  • 14+ years in software/data engineering; BS/MS in CS/Engineering (or equivalent experience).
  • Strong hands-on coding in Python and SQL (Java/Scala a plus).
  • Proven delivery of lakehouse/data platform solutions using Databricks and/or Snowflake on AWS (GCP or Azure acceptable).
  • Strong Spark (batch/streaming) development and performance/cost tuning.
  • Experience with Apache Iceberg and table/catalog governance concepts (e.g., Unity Catalog or equivalent).
  • Production engineering practices: CI/CD, IaC (Terraform/CloudFormation), automated testing, security basics, and observability.
  • Ownership mindset for operations: on-call/incident response, RCA, backfills, and reliability improvements; strong communication with global teams.

Preferred Qualifications

  • Financial services experience (asset management preferred).
  • Experience across structured + alternative/unstructured data, plus governance tooling (Snowflake Horizon/Unity Catalog/Collibra/Alation or similar).
  • Use of AI-assisted coding tools (e.g., GitHub Copilot, Claude Code) while maintaining code quality.

About State Street

Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.


We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.


As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.


Discover more information on jobs at StateStreet.com/careers


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How we rate this

Data Platform - Capability Engineer - Assistant Vice President at State Street rates 60 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Data EngineeringCloud ArchitectureData GovernanceDistributed ComputingClaudeCopilotDatabricksClaude Code

Questions you could be asked

  1. Tell me about a project where data engineering was part of your work. What did you do?
  2. Tell me about a project where cloud architecture was part of your work. What did you do?
  3. Tell me about a project where data governance was part of your work. What did you do?
  4. Tell me about a project where distributed computing was part of your work. What did you do?
  5. Walk me through how you've used Claude in your day-to-day work.

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  • List these exact terms on your resume: Data Engineering, Cloud Architecture, Data Governance, Distributed Computing, and Claude. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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