Senior Data Engineer Fraud Analytics
Posted
Title: Senior Data Engineer Fraud Analytics
Location: Merrimack NH / Smithfield RI
On-site/Remote/Hybrid: Onsite
Duration: 6-12 Months
Interview Process: 2 Rounds
No of submissions:
No of Positions:
Top Skills
The Role
The Senior Data Engineer Fraud Analytics is responsible for designing, building, and maintaining data solutions that support the research, detection, and analysis of fraud events. This role partners closely with fraud analysts, investigators, and business stakeholders to transform large, complex datasets into actionable insights that reduce fraud risk and improve detection strategies.
Key Responsibilities
Design, develop, and optimize data pipelines to support fraud research and analytics use cases
Research and analyze fraud events by querying and correlating structured and unstructured data across multiple platforms
Write complex, high-performance SQL queries to extract, transform, and analyze large datasets
Work extensively with Oracle databases to support enterprise-scale fraud analytics
Utilize MongoDB for handling semi-structured and unstructured fraud-related data
Investigate data anomalies, identify fraud patterns, and support root-cause analysis
Partner with fraud operations, compliance, and analytics teams to translate business questions into technical data solutions
Ensure data accuracy, consistency, and reliability across fraud datasets
Document data models, logic, and findings clearly for both technical and non-technical audiences
Communicate findings effectively through written reports, presentations, and stakeholder
discussions
Support continuous improvement of fraud detection and monitoring processes through data-driven insights
The Expertise and Skills You Bring
Required Skills
5+ years of experience in data engineering, analytics, or a related technical role
Advanced proficiency in SQL, including complex joins, subqueries, performance tuning, and data validation
Strong hands-on experience with Oracle databases
Working knowledge of MongoDB or similar NoSQL technologies
Experience researching fraud events, financial anomalies, risk signals, or suspicious activity
(preferred)
Strong analytical and problem-solving skills with attention to detail
Excellent written and verbal communication skills, with the ability to explain technical findings to business partners
Ability to work independently while collaborating across cross-functional teams
Preferred Qualifications
Experience supporting fraud, risk, compliance, or financial crime analytics
Familiarity with large-scale data environments and data warehousing concepts
Exposure to scripting or data-processing languages such as Python (nice to have)
Experience working in regulated or financial services environments
Strong critical thinking and investigative mindset
Ability to prioritize and manage multiple research efforts simultaneously
Comfortable working with ambiguity and incomplete data
Collaborative, proactive, and detail-oriented
About Us:
InterSources Inc, is a Small, Woman, and Minority-Owned Business Enterprise, ISO/IEC 27001, SOC 2 Type 2 certified company with massive 18+ years of diversified experience in providing IT Consulting Services, Artificial Intelligence, Data Analysis, Application Development, Cloud Services, Cybersecurity, Digital Marketing, ERP Management, Custom Software Development, Web Development, UI/ UX Design, System Integration, QA Support etc. We make reasonable accommodations for clients and employees, and we do not discriminate based on any protected attribute including race, religion, color, national origin, gender sexual orientation, gender identity, age, or marital status. We also are a Google Cloud and Oracle partner company.
Location: Merrimack NH / Smithfield RI
On-site/Remote/Hybrid: Onsite
Duration: 6-12 Months
Interview Process: 2 Rounds
No of submissions:
No of Positions:
Top Skills
- Design, develop, and optimize data pipelines to support fraud research and analytics use cases
- Research and analyze fraud events by querying and correlating structured and unstructured data across multiple platforms
- Write complex, high-performance SQL queries to extract, transform, and analyze large datasets
- Work extensively with Oracle databases to support enterprise-scale fraud analytics
- Utilize MongoDB for handling semi-structured and unstructured fraud-related data
The Role
The Senior Data Engineer Fraud Analytics is responsible for designing, building, and maintaining data solutions that support the research, detection, and analysis of fraud events. This role partners closely with fraud analysts, investigators, and business stakeholders to transform large, complex datasets into actionable insights that reduce fraud risk and improve detection strategies.
Key Responsibilities
Design, develop, and optimize data pipelines to support fraud research and analytics use cases
Research and analyze fraud events by querying and correlating structured and unstructured data across multiple platforms
Write complex, high-performance SQL queries to extract, transform, and analyze large datasets
Work extensively with Oracle databases to support enterprise-scale fraud analytics
Utilize MongoDB for handling semi-structured and unstructured fraud-related data
Investigate data anomalies, identify fraud patterns, and support root-cause analysis
Partner with fraud operations, compliance, and analytics teams to translate business questions into technical data solutions
Ensure data accuracy, consistency, and reliability across fraud datasets
Document data models, logic, and findings clearly for both technical and non-technical audiences
Communicate findings effectively through written reports, presentations, and stakeholder
discussions
Support continuous improvement of fraud detection and monitoring processes through data-driven insights
The Expertise and Skills You Bring
Required Skills
5+ years of experience in data engineering, analytics, or a related technical role
Advanced proficiency in SQL, including complex joins, subqueries, performance tuning, and data validation
Strong hands-on experience with Oracle databases
Working knowledge of MongoDB or similar NoSQL technologies
Experience researching fraud events, financial anomalies, risk signals, or suspicious activity
(preferred)
Strong analytical and problem-solving skills with attention to detail
Excellent written and verbal communication skills, with the ability to explain technical findings to business partners
Ability to work independently while collaborating across cross-functional teams
Preferred Qualifications
Experience supporting fraud, risk, compliance, or financial crime analytics
Familiarity with large-scale data environments and data warehousing concepts
Exposure to scripting or data-processing languages such as Python (nice to have)
Experience working in regulated or financial services environments
Strong critical thinking and investigative mindset
Ability to prioritize and manage multiple research efforts simultaneously
Comfortable working with ambiguity and incomplete data
Collaborative, proactive, and detail-oriented
About Us:
InterSources Inc, is a Small, Woman, and Minority-Owned Business Enterprise, ISO/IEC 27001, SOC 2 Type 2 certified company with massive 18+ years of diversified experience in providing IT Consulting Services, Artificial Intelligence, Data Analysis, Application Development, Cloud Services, Cybersecurity, Digital Marketing, ERP Management, Custom Software Development, Web Development, UI/ UX Design, System Integration, QA Support etc. We make reasonable accommodations for clients and employees, and we do not discriminate based on any protected attribute including race, religion, color, national origin, gender sexual orientation, gender identity, age, or marital status. We also are a Google Cloud and Oracle partner company.
