trade volume patterns, and rebalancing activity signals.
Flink Analytics Architecture: Architect the Apache Flink deployment downstream
of Gold topics for real-time cross-client aggregations - windowed rollups (5-
min/hourly/daily), complex event processing (unusual trading activity patterns), and
streaming joins across entity types.
Federated ML Architecture: Design the architecture for federated ML models using
federated learning frameworks - local training on each client ODS, gradient
aggregation in confidential enclaves, differential privacy on gradient updates to
prevent gradient inversion attacks. Define use cases: cross-client anomaly
detection, industry-wide risk signal models, shared compliance patterns.
Feature Store Architecture: Architect the Feature Store (Hopsworks/Feast)
integration - how Flink-computed features (sliding window calculations) are served
for both batch training and real-time inference at sub-millisecond latency.
Confidential Compute Vendor Evaluation: Lead the technical evaluation of Azure
Confidential Clean Rooms vs. Opaque Systems. Define evaluation criteria, run pilot
architectures for both, and make a vendor recommendation based on maturity,
financial services fit, and long-term strategic alignment.
Privacy Budget Management: Design the privacy budget framework - how epsilon
budgets are allocated across query types, time windows, and clients. Ensure that
cumulative privacy loss remains within acceptable bounds over time.
Regulatory Architecture: Ensure the aggregated analytics architecture supports
GDPR right-to-erasure, DORA ICT risk monitoring, and BCBS 239 risk data
aggregation reporting. Design consent management integration for cross-client data
participation.
Standards & Governance: Establish data modelling standards, privacy review
processes, and architecture review gates for all Aggregated Analytical Warehouse
development.
Requirements
Education: Bachelor's or Master's degree in Computer Science, Engineering,
Mathematics, Statistics, or a related technical field. Advanced degree preferred.
Experience: 8+ years of experience in data architecture or data engineering, with at
least 3 years in a data architect role. Experience with multi-party or crossinstitutional data architectures.
Privacy Technologies: Strong understanding of differential privacy (epsilon-DP),
confidential computing (AMD SEV-SNP, Intel SGX), and federated learning/analytics
concepts. Ability to design systems that provide formal privacy guarantees.
Microsoft Fabric / Azure: Deep experience with Microsoft Fabric, Azure Synapse, or
equivalent cloud ana
Additional Information
Job Title: Data Architect - Aggregated Analytical Warehouse (FNZ)
About FNZ:
FNZ is a global fintech firm transforming the way financial institutions serve their clients. By
combining cutting-edge technology, infrastructure, and investment operations, FNZ
enables wealth management firms to deliver personalized investment solutions at scale.
Operating across multiple regions and supporting over $1.5 trillion in assets under
administration, FNZ partners with leading banks, insurers, and asset managers to create
seamless and innovative wealth platforms that empower millions of investors worldwide.
Job Summary:
We are seeking a Data Architect to design and own the architecture of the Aggregated
Analytical Warehouse - FNZ's cross-client analytics platform that delivers industry-level
benchmarks, risk signals, and aggregated insights with mathematically guaranteed privacy.
This role architects the three-layer privacy stack (federated architecture, confidential
compute, differential privacy) and defines how aggregated analytics are modelled,
computed, and served. This is one of the most architecturally novel roles on the platform,
as no competitor in wealth management offers cross-client analytics with this level of
privacy assurance.
Fnz · Pune Job Posting Location -, India