Platform Engineering Lead

FNZ (UK) Ltd; Pune District; On-site; INR 3,000,000 - 4,600,000; Full time

Job summary

FNZ (UK) Ltd is seeking a Platform Engineering Lead to drive delivery of the data platform spanning NRT-ODS, Analytical Warehouse on Microsoft Fabric, and AI capabilities. You will lead engineering teams, ensure platform security, and orchestrate cross-functional delivery across data trust, governance, and client data delivery.

The role demands 10+ years in data engineering with hands-on Kafka and lakehouse experience, and strong leadership in an Azure/Kubernetes environment.

Qualifications

• 10+ years in software/data engineering with leadership experience.
• Deep Kafka expertise: design, partitioning, CDC patterns.
• Hands-on with modern lakehouse ecosystems and cloud infra.

Responsibilities

• Lead delivery of the data platform across NRT-ODS, warehousing, and AI capabilities.
• Drive performance, reliability, and security across the stack.
• Mentor engineers, set standards, and oversee roadmap execution.
• Collaborate with product and executives to translate plans into deliverables.

Skills

Leadership

Kafka Streams

Apache Kafka

Data Platform

Azure Cloud

Platform Security

Team Leadership

DevOps

Flink

AI/ML Basics

Education

Bachelor's degree in Computer Science or Engineering

Master's degree in Computer Science or Engineering

Tools

Kubernetes

ArgoCD

Backstage

Debezium

Conduktor

Apicurio Registry

Delta Lake

Apache Iceberg

Flink

Job description

Job Title: Platform Engineering Lead (FNZ)About FNZ:FNZ is a global fintech firm transforming the way financial institutions serve their clients. Bycombining cutting-edge technology, infrastructure, and investment operations, FNZenables wealth management firms to deliver personalized investment solutions at scale.Operating across multiple regions and supporting over $1.5 trillion in assets underadministration, FNZ partners with leading banks, insurers, and asset managers to createseamless and innovative wealth platforms that empower millions of investors worldwide.Job Summary:We are seeking an experienced Platform Engineering Lead to drive the engineering deliveryof FNZ's data platform. This role leads engineering efforts across the full platform scope —the Near Real-Time Operational Data Store (NRT-ODS), Analytical Warehouse, AI/MLcapabilities, and Platform Security. The ideal candidate will own the technical delivery thatevolves the platform from a data delivery engine into an industry-leading insight platform,leading engineering teams across roadmap pillars including Data Trust & Governance,Client Data Delivery, Lakehouse & Fabric Integration, Stream Processing, Intelligence & AI,Cross-Client Analytics, and Operational Excellence.Key Responsibilities:• Engineering Leadership: Lead engineering delivery across the entire data platform— NRT-ODS streaming platform, Analytical Warehouse (Microsoft Fabric), AI/MLlayer, and platform security. Drive execution, remove blockers, and ensureengineering quality across all pillars of the platform roadmap.• ODS Engineering Delivery: Own the engineering delivery of the streaming-first,event-driven platform comprising 179 Kafka Streams topologies, Debezium CDCpipelines, 200+ Avro schemas (Apicurio Registry), OAuth 2.0 security (KeyCloak),and Kubernetes-based deployment. Drive performance tuning, reliabilityimprovements, and feature delivery.• Analytical Warehouse Delivery: Lead the engineering build-out of the AnalyticalWarehouse on Microsoft Fabric, including Kafka-to-Fabric Direct Sink,Delta/Parquet storage on OneLake, semantic layer, and future Apache Icebergadoption for time-travel queries and multi-engine access.• AI & Intelligence Delivery: Drive the engineering delivery of AI capabilities includingFeature Store (Hopsworks/Feast), RAG over ODS documentation and schemas,NL2SQL for Gold data, and domain-specific ML models. Ensure Flink-poweredfeature computation pipelines are delivered to production.• Platform Security Delivery: Lead engineering efforts for platform security spanningOAuth 2.0, Conduktor Gateway, TLS, Kafka ACLs, multi-tenant isolation,confidential compute (Azure Confidential Clean Rooms / Opaque Systems), anddifferential privacy (SmartNoise/OpenDP) for cross-client analytics.• Data Trust & Governance: Drive delivery of data contracts on Gold schemas,pipeline validation (Great Expectations/Soda), end-to-end data lineage, automatedanomaly detection, and regulatory automation (PII classification, DORA, BCBS 239,GDPR).• Client Delivery Engineering: Lead engineering for multiple delivery patterns —streaming SDK (Vanguard), batch extract (BMO), MirrorMaker 2, WebSocket/SSEgateway, self-service client portal, and the Wealth-as-a-Service API (REST +GraphQL).• Cross-Client Analytics: Drive engineering delivery of the three-layer privacy stack— federated processing (data never leaves client boundary), confidential compute(hardware-attested enclaves), and differential privacy on all outputs. Lead federatedlearning implementation using federated learning frameworks.• Stream Processing Engineering: Lead the dual-engine strategy — Kafka Streamsfor CDC processing and enrichment, Apache Flink for analytical stream processing(windowed aggregations, complex event patterns, streaming SQL). Driveperformance optimization and operational stability.• Technology Evaluation & Selection: Lead build-vs-buy decisions across theplatform — data lineage (Atlan vs. Purview vs. custom), observability (Monte Carlovs. custom), confidential compute (Opaque Systems vs. Azure Clean Rooms),developer portal (Backstage vs. custom). Own proof-of-concept delivery and vendorevaluation.• Team Leadership: Lead and mentor data engineers, platform engineers, andspecialists across the data platform. Set engineering standards, conduct code anddesign reviews, and foster a high-performance engineering culture.• Stakeholder Management: Work with product owners and executive stakeholdersto translate roadmap priorities into engineering plans, align delivery timelines withclient commitments (Vanguard, BMO, RJ), and communicate progress and risks.• Engineering Excellence: Establish and enforce engineering standards — CI/CDpractices (GitHub Actions, ArgoCD), testing strategies, observability(Grafana/Prometheus), incident response, and operational runbooks across allplatform teams.Qualifications:• Education: Bachelor's or Master's degree in Computer Science, Engineering, or arelated technical field.• Experience: 10+ years of experience in software/data engineering, with at least 5years leading engineering teams delivering large-scale data platforms.• Streaming Platforms: Deep hands-on expertise with Apache Kafka — topic design,partitioning strategies, Kafka Streams, Kafka Connect, schema registries, and CDCpatterns (Debezium).• Analytical Platforms: Strong experience building and delivering modern lakehouseplatforms — Microsoft Fabric, Delta Lake, Apache Iceberg, Parquet, and semanticlayers and data transformation frameworks.• Cloud & Infrastructure: Extensive experience delivering on Azure (AKS, OneLake,Fabric, Key Vault, Managed Identities) with Kubernetes-based deployments.• Platform Security: Deep understanding of OAuth 2.0, TLS, network segmentation,multi-tenant isolation, and data encryption patterns in financial servicesenvironments.• AI/ML Platforms: Working knowledge of feature stores, RAG implementations,vector databases, and ML serving infrastructure.• Data Governance: Experience delivering data contracts, data lineage, data qualityframeworks, and regulatory compliance solutions (DORA, BCBS 239, GDPR).• Engineering Leadership: Proven track record of leading cross-functionalengineering teams, delivering against roadmaps, managing technical debt, anddriving engineering excellence.Preferred Qualifications:• Experience working in the Wealth Management or Financial Services industry withstrong emphasis on data governance and regulatory compliance.• Experience with privacy-preserving technologies — confidential compute,differential privacy, federated learning.• Hands-on experience with Apache Flink for analytical stream processing alongsideKafka Streams.• Experience with GitOps (ArgoCD), Helm umbrella charts, and platform engineeringpractices (Backstage).• Track record of delivering platforms that serve multiple clients with distinctdelivery patterns (streaming, batch, API).• Experience with agile delivery at scale — sprint planning, backlog management,cross-team coordination, and delivery reporting.• Relevant certifications (Azure, Confluent Kafka) are a plus.*About FNZ**FNZ is committed to opening up wealth so that everyone, everywhere can invest in their future on their terms. We know the foundation to do that already exists in the wealth management industry, but complexity holds firms back.**We created wealth’s growth platform to help. We provide a global, end-to-end wealth management platform that integrates modern technology with business and investment operations. All in a regulated financial institution.**We partner with the world’s leading financial institutions, with over US$2.4 trillion in assets on platform (AoP). Together with our clients, we empower nearly 30 million people across all wealth segments to invest