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Senior Data Engineer – AI & Automation, Vice president

Job in Bengaluru, 560001, Bangalore, Karnataka, India
Listing for: State Street
Full Time position
Listed on 2026-03-07
Job specializations:
  • IT/Tech
    Data Engineer, Data Analyst, Data Science Manager, Data Security
Job Description & How to Apply Below
Position: Senior Data Engineer – AI & Intelligent Automation, Vice president
Location: Bengaluru

This job is with State Street, an inclusive employer and a member of my Gwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

Role Overview
We are hiring a  senior, hands-on Data Engineer  to play a pivotal role in transforming Global Delivery operations through  data-driven automation, generative AI, and agent-based systems . This is  not a traditional data engineering role .
This role sits at the intersection of  data engineering, AI enablement, and business simplification , owning the end-to-end data foundation that powers intelligent workflows used directly in core operational processes. You will act as the  data owner and steward  for high-impact simplification initiatives, ensuring data quality, control, auditability, and fitness-for-purpose across analytics, automation, and AI decisioning.
You will work closely with Product Owners, AI engineers, and platform teams to design and operate  production-grade data pipelines and data products  that enable scalable, secure, and observable AI-driven workflows across the asset servicing lifecycle.

Key Responsibilities
Design, build, and operate  scalable, resilient data pipelines  supporting operational analytics, reporting, and AI-driven automation across cloud and on‑prem environments.

Model, store, and serve  large-scale datasets  optimized for both analytical workloads and  low-latency consumption by AI and agent-based systems .

Integrate data from  multiple internal and external sources , including vendor feeds, APIs, files, and enterprise platforms.

Ensure pipelines are observable, reliable, and production-ready with clear ownership and operational rigor.

Act as  Data Steward  for assigned business services within GD Simplification, accountable for:
Data quality, consistency, lineage, and lifecycle management

Business definitions, critical data elements (CDEs), and calculation logic

Data dictionaries, business glossaries, and metadata

Define and enforce  data standards, controls, and documentation  aligned with governance and platform requirements.

Translate business control requirements into  data-level and AI control mechanisms .

AI & Agentic Systems Enablement
Enable AI and intelligent automation by ensuring  high-quality, well-governed inputs  for training, inference, and decisioning.

Define  agent action constraints , data quality gates, and  human‑in‑the‑loop triggers  before automated actions are executed.

Ensure  auditability and traceability  through agent decision logs, data lineage, and versioning of rules, prompts, and models.

Data Quality, Controls & Operations
Establish data quality rules and exception taxonomies.

Monitor data quality dashboards, triage issues, and coordinate remediation across upstream and downstream teams.

Ensure data quality and control checks are embedded  before AI-driven actions  occur.

Align data architecture and integrations with broader ecosystem dependencies, cost considerations, and execution plans.

Collaboration & Influence
Partner closely with Product Owners to ensure data definitions and metrics align with  business intent and measurable outcomes .

Collaborate across engineering, AI, platform, and business teams to identify and prioritize  high-value simplification and automation use cases .

Communicate complex technical concepts clearly to non-technical stakeholders and help drive adoption of AI-enabled solutions across GD.

Champion modern data and engineering practices across organizational boundaries.

Required Skills & Experience
5-10+ years of hands-on experience in  data engineering , preferably in platform, infrastructure, or large-scale enterprise environments.

Strong engineering and systems mindset with experience building  production-grade data pipelines .

Deep understanding of  data lifecycle management , data quality, metadata, and controls in regulated environments.

Experience working closely with business stakeholders in complex operational domains (e.g., fund accounting, middle office, custody, payments, transfer agency).

Strong SQL skills for data validation and analysis.

Working knowledge of Python (or similar) for data processing, automation, or…
Position Requirements
10+ Years work experience
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