Data Architect – Fraud / OMAI Role Overview
Photon is looking for a hands-on Data Architect to support large-scale Fraud and AI-led transformation initiatives within the financial services industry.
The role will focus on designing an integrated data ecosystem that brings together customer, account, transaction, payment, channel, device, behavioral, and fraud data into a consistent and scalable architecture.
The ideal candidate will have strong experience designing and implementing large-scale enterprise data platforms, primarily within on-premise / distributed Big Data environments, and should be comfortable working directly with engineering teams on data models, data flows, integration patterns, and implementation.
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.
Required Experience
- Strong experience as a hands-on Data Architect / Lead Data Engineer / Data Solution Architect within large-scale financial services or enterprise environments.
- Strong experience working with customer, account, transaction, payment, and relationship data.
- Deep understanding of Big Data and distributed data processing architectures.
- Hands-on experience with technologies such as Hadoop, Spark, Kafka, and related distributed data technologies.
- Strong experience with SQL, data modeling, data transformations, and large-scale data processing.
- Experience designing high-volume batch and real-time / event-driven data architectures.
- Strong understanding of ETL/ELT, APIs, messaging, data ingestion, transformation, and integration patterns.
- Experience integrating data across legacy platforms, relational databases, distributed data platforms, and enterprise applications.
- Strong conceptual, logical, and physical data modeling experience.
- Understanding of data governance, lineage, metadata, data quality, security, and privacy within regulated environments.
- Ability to move beyond architecture diagrams and work directly with engineering teams to validate designs, solve implementation issues, and drive solutions through delivery.
Preferred Experience
- Experience within Fraud, Payments, Retail Banking, Cards, Financial Crime, or Customer Data domains.
- Understanding of fraud use cases including transaction monitoring, behavioral analytics, customer identity, device intelligence, fraud detection, and investigation.
- Experience creating Customer 360 / unified customer data architectures across complex enterprise environments.
- Exposure to data architectures supporting AI/ML, feature engineering, model execution, and real-time decisioning.
- Experience with large-scale data modernization, platform consolidation, or data transformation programs.
Key Profile We Are Looking For
A hands-on Data Architect who can get into the data and technology, understand where customer and fraud information resides across a complex financial ecosystem, and define how it should be brought together.
The individual should be able to answer:
Where is the data? How is it connected? How should it move? How should it be modeled? And how do we make it reliably available at scale for Fraud, analytics, AI/ML, and operational decisioning?
Compensation, Benefits and Duration
Minimum Compensation: USD 53,000
Maximum Compensation: USD 188,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full-time employees.
This position is not available for independent contractors
No applications will be considered if received more than 120 days after the date of this post.