> Markdown version of [/jobs/ext/3733714-data-architect-with-fraud-reporting-and-analytics](https://www.wearedevelopers.com/jobs/ext/3733714-data-architect-with-fraud-reporting-and-analytics). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Architect with Fraud reporting and Analytics

- **Company:** Tanisha Systems Inc
- **Location:** Jacksonville, FL, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Business Intelligence Development, Big Data, Information Systems, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Transformation, Data Warehousing, Executive Information Systems, Fraud Prevention and Detection, Apache Hadoop, IBM Cognos Business Intelligence, Machine Learning, Meta-Data Management, Performance Tuning, Cloud Services, Standard Sql, SAS (Software), PL-SQL, Data Streaming, Qliksense, Google Cloud, Azure Data Factory, Apache Spark, Togaf, Data Lakes, Information Technology, Qlikview, AWS Data Analytics, Tools for Reporting, Actimize, Data Pipelines, Databricks
- **Published:** October 14, 2026
- **Apply:** https://www.dice.com/job-detail/cd6f501d-313d-4ea7-b409-32c6c6723eaf

## About the Role

Technical
Strong expertise in Enterprise Data Architecture and Data Modeling.
Extensive experience in Data Warehousing, ETL/ELT, Data Lakes, and Analytics Platforms.
Hands-on knowledge of SQL, PL/SQL, and performance optimization of large datasets.
Experience with reporting and visualization platforms such as:
Power BI
Tableau
Cognos
QlikView/Qlik Sense
Experience with cloud data platforms:
Azure Data Platform
AWS
Google Cloud Platform (preferred)
Knowledge of Hadoop, Spark, Databricks, and modern data engineering frameworks.
Understanding of data governance, lineage, metadata management, and data quality frameworks.
Domain
Strong experience in Banking and Financial Services.
Proven background in:
Fraud Detection & Prevention
Transaction Monitoring
Fraud Operations Analytics
Risk & Control Reporting
Financial Crime / AML Reporting
Understanding of regulatory and compliance reporting requirements in financial institutions.
Preferred Skills
Experience with fraud platforms such as NICE Actimize, SAS Fraud Management, FICO Falcon, or equivalent.
Exposure to AI/ML-driven fraud analytics and anomaly detection frameworks.
Experience architecting real-time streaming and event-based analytics solutions., Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or related field.
TOGAF, Azure Data Architect, AWS Data Analytics, or equivalent certifications preferred.
Key Success Factors
Strong stakeholder management and communication skills.
Ability to influence senior business and technology leaders.
Experience leading large-scale banking data transformation programs.
Ability to balance architecture governance with delivery agility.

## Description

We are seeking an experienced Data Architect with strong expertise in Fraud Reporting, Analytics Platforms, Data Warehousing, and Enterprise Data Architecture within the banking domain. The ideal candidate will lead the design and implementation of scalable data solutions supporting fraud detection, transaction monitoring, regulatory reporting, risk analytics, and executive dashboards., Design and implement enterprise-scale data architectures supporting Fraud, Risk, and Compliance reporting platforms.
Define logical and physical data models for fraud analytics, transaction monitoring, alert management, and case management systems.
Architect and optimize data lakes, data warehouses, and reporting solutions to enable near real-time fraud insights.
Collaborate with business stakeholders, fraud operations teams, data scientists, and technology teams to translate business requirements into scalable data solutions.
Drive data governance, lineage, metadata management, and data quality initiatives across fraud data domains.
Design integration frameworks between source systems, fraud platforms (e.g., Actimize, SAS, FICO), reporting tools, and downstream analytics applications.
Support regulatory and management reporting requirements related to fraud, AML, financial crime, and operational risk.
Ensure architecture compliance with enterprise security, privacy, and data governance standards.
Provide architectural guidance for cloud migration and modernization initiatives.