State Street Corporation
Create a free account
One signup unlocks everything for this job:
- Apply to this job and track your application
- See your personalized profile match score
- Generate an AI cover letter for this role
Bengaluru · On-site · 1-3 Yrs · Aug 21
Investment & Asset Management · 10000+ Employees · Boston, US
Working for State Street in India, you'll support the effective delivery of services to our clients as part of an international operation. As our business continues to grow, we are building a platform that combines local expertise and significant scale to deliver the highest levels of service to clients across the region and beyond. The pace and scope of our operation makes for a challenging yet exciting working environment, where management is open to new ideas and committed to innovation. Flexibility is key as we work to meet the rapidly changing needs of our institutional client base. You'll have multiple opportunities to gain experience in diverse aspects of the investment cycle. The continuous development of our employees is important as we strive to rapidly build our local management team and create future leaders from within.
Hiring: Engineering
What employees say
+ No pros , you might get a good friend if you are lucky
− Overtime work, with no over time pay. Always they provide over work. No social life due to workload. Health issues .
More reviews on the company profile.
Interview experience · Financial Reporting Analyst
My interview experience was good. There were 2-3 panellists and had 2 rounds. First round was purely technical asking about my field of work as well areas from job description. The 2nd round was predominantly questions o
Difficult difficulty · India · 314 reports
More interview insightsJob description
Overview
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.
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.
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.
- 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.
- Use of AI-assisted coding tools (e.g., GitHub Copilot, Claude Code) while maintaining code quality.
Nice to have
- Financial services experience (asset management preferred).
Verify Python for this role
Free PRACTICE for Python adds a verified skill signal that can boost how roles like this rank for you — optional, not required to browse or apply.
Sign up — verify Python free →Want match scores and deeper insight? Create a free candidate profile