Data Architect / Engineer - Assistant Vice President
State Street is hiring a Data Architect / Engineer - Assistant Vice President in Bengaluru, India. Level rates it ; you can apply on Level.
AI in this role
We are looking for an experienced Data Architect / Data Engineer, Assistant Vice President to provide technical and architectural leadership for enterprise cybersecurity data, analytics, and AI capabilities.
This role will define and deliver scalable data architectures, Lakehouse platforms, data models, integration frameworks, and AI-ready data foundations. The individual will partner with cybersecurity, engineering, architecture, governance, risk, and product teams to transform complex security data into scalable, governed, and actionable solutions.
What you will be responsible forAs a Data Architect / Engineer, you will:
· Architect and deliver scalable Lakehouse and enterprise data platforms, pipelines, data models, and reusable data products.
· Define target-state data architecture, reference architectures, integration patterns, standards, and technical roadmaps.
· Design solutions for large-scale structured, semi-structured, time-series, graph, and unstructured cybersecurity data.
· Establish reusable frameworks for ETL/ELT, ingestion, orchestration, data quality, metadata, lineage, observability, and reconciliation.
· Establish architecture standards for scalability, resiliency, performance, security, privacy, governance, and auditability.
· Design AI-ready data architectures supporting LLMs, RAG, embeddings, vector/semantic search, NLP, knowledge graphs, and intelligent workflows.
· Integrate data across cloud platforms, enterprise systems, cybersecurity platforms, and SIEM/SOAR ecosystems.
· Provide technical leadership through architecture reviews, engineering standards, technology evaluation, and solution governance.
· Partner with stakeholders to translate cybersecurity and business requirements into scalable data and AI solutions.
· Mentor engineering teams and drive reusable architecture patterns, automation, and engineering best practices.
What we value
These skills will help you succeed in this role:
· Strong expertise in Data Architecture, Data Engineering, Cloud Data Platforms, and AI/GenAI.
· Deep understanding of Lakehouse architecture, distributed processing, ETL/ELT, data modeling, integration, data quality, metadata, lineage, and governance.
· Strong hands-on skills in Python, SQL, PySpark, Databricks, Delta Lake, and cloud technologies.
· Experience designing enterprise-scale, secure, resilient, and governed data platforms.
· Practical knowledge of LLMs, RAG, embeddings, vector/semantic search, NLP, knowledge graphs, and responsible AI architecture.
· Understanding of cybersecurity telemetry, SIEM/SOAR, vulnerability management, identity risk, threat intelligence, and incident data.
· Ability to influence architecture decisions and engage effectively with technical teams, architects, product leaders, and senior stakeholders
Education & QualificationsMinimum Qualifications
· 15+ years of experience across Data Architecture, Data Engineering, enterprise data platforms, cloud, analytics, AI, or related technology disciplines.
· Bachelor's degree in Computer Science, Engineering, Information Systems, Cybersecurity, or a related discipline, or equivalent experience.
· Proven experience architecting and delivering enterprise-scale data platforms and Lakehouse solutions.
· Strong experience with Python, SQL, PySpark, Databricks, ETL/ELT, distributed processing, data modeling, and AWS or comparable cloud platforms.
· Experience with CI/CD, automated testing, monitoring, data governance, and engineering best practices.
· Experience in cybersecurity, financial services, regulated industries, or large enterprise environments is highly desirable
· Strong written, verbal, analytical, and stakeholder communication skills.
Technical Skills
Skill Area
Expected Capabilities
Data Architecture
Lakehouse, enterprise data modeling, data domains, data products, data contracts, integration patterns, reference architecture, metadata and governance
Data Engineering
Python, SQL, PySpark, Databricks, Delta Lake, ETL/ELT, orchestration, data quality, lineage and observability.
AI & Gen AI
LLMs, RAG, embeddings, vector/semantic search, NLP, knowledge graphs, responsible AI and AI-enabled workflows.
Cloud & DevOps
AWS, CI/CD, Git, automated testing and scalable cloud data processing
Cybersecurity Data
SIEM/SOAR, security telemetry, vulnerability, identity, incident and threat intelligence data.
Visualization & BI
Power BI, semantic models, operational metrics and executive reporting.
Additional Requirements· This is an individual contributor role with strong cross-functional collaboration expectations.
· The role will require sound judgment when working with sensitive cybersecurity, risk, operational, and regulated data.
· The candidate should be comfortable balancing exploratory data science, production-minded analytical delivery, and stakeholder communication.
Why this role is important to usCybersecurity increasingly depends on the ability to engineer, integrate, analyze, and intelligently interpret large volumes of complex security data. This role will bridge Data Engineering, Data Science, Cybersecurity, and AI, building trusted data foundations and intelligent solutions that improve threat detection, risk prioritization, security operations, and enterprise decision-making.About State StreetState Street is one of the world's leading providers of financial services to institutional investors, including investment servicing, investment management, investment research, and trading. Technology and cybersecurity are critical enablers of our ability to safeguard information, support clients, and operate at enterprise scale.
We value collaboration, innovation, inclusion, and responsible technology. We are looking for technical talent who can solve meaningful problems, communicate clearly, and help build secure, scalable, data-driven capabilities for the future.
State Street is an equal opportunity and affirmative action employer.
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 Architect / Engineer - Assistant Vice President at State Street rates 72 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.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ 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
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- How do you think about the risk of an AI system in this kind of role failing silently?
- What's a project where you used Databricks hands-on?
- Describe a typical day in a role like this one: which parts run through AI directly?
Adapt your resume
- List these exact terms on your resume: RAG, NLP, AI Safety, and Databricks. 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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