Data Architect

Hi Everyone,

We are Photon, one of the world's largest Digital Platform Engineering companies providing a combination of Strategy Consulting, Creative Design and Technology Services to a wide range of customers. We work with 40% of the Fortune 100 companies.

For a brief 1 minute video about us, you can check https://youtu.be/uJWBWQZEA6o.

About the Role:

Key Responsibilities

• Define and drive the data architecture for Fraud, integrating customer, account, transaction, payment, channel, device, behavioral, and fraud-related data across multiple source systems.
• Design an ecosystem that enables a unified view of customer relationships, transactions, interactions, and fraud signals.
• Work hands-on with engineering teams to define data models, data structures, data flows, ingestion patterns, transformation logic, and consumption patterns.
• Architect scalable solutions for high-volume and high-velocity data using distributed Big Data technologies.
• Design batch, near-real-time, and streaming data pipelines supporting fraud detection, monitoring, analytics, and decisioning.
• Define conceptual, logical, and physical data models across customer and fraud domains.
• Establish integration patterns across legacy systems, enterprise data platforms, APIs, messaging, and distributed data environments.
• Review existing data platforms and identify opportunities to simplify data movement, eliminate duplication, improve accessibility, and establish trusted data sources.
• Partner with Fraud, Data, Engineering, AI/ML, Risk, and Architecture teams to translate business requirements into implementable technical solutions.
• Ensure appropriate data quality, lineage, metadata, security, privacy, traceability, and governance controls.
• Support data consumption for fraud analytics, AI/ML models, operational workflows, investigations, and real-time decisioning.
• Provide technical leadership through design, development, implementation, performance tuning, and production rollout.

Qualification

• Experience designing and implementing a "Data as a Product" strategy, treating data assets as discoverable, trusted, and consumable products across the organization
• Familiarity with modern data architecture techniques, including lakehouse architectures and ETL-free approaches such as data virtualization or data mesh
• Fraud domain experience is a plus

Education

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related technical field required