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Big Data Engineer - AI/ML and Fraud Strategy

• Posted 6 hours ago • Updated 6 hours ago

Contract W2

75% Travel Required

Fitment

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Job Details

Skills

databricks
Data Quality
Machine Learning
Big Data
Apache Spark
Apache Kafka
Data Architecture
Data Warehousing
Data Pipelines
Governance
microservices
Artificial Intelligence
Requirements Analysis
PySpark
Anomaly Detection
Amazon Web Services
Risk Analysis
Architecture
Safety Principles
Technology Roadmaps
Application Programming Interfaces (APIs)
Communication Skills
Python (Programming Language)
Knowledge of Finance
Amazon S3
SQL Databases
Cloud Services
Data Lakes
Banking Services
Machine Learning Operations
Data Streaming
Technical Management
Technology Strategies
Kinesiology
Apache Hadoop
Governance Risk Management and Compliance
Monitoring of Systems
Event Driven Architecture
Fintech
Debits and Credits
Behavioral Targeting
Feature Engineering
Fraud Prevention and Detection
Google Wallet
Processing of Payments
Risk Measure

databricks
Data Quality
Machine Learning
Big Data
Apache Spark
Apache Kafka
Data Architecture
Data Warehousing
Data Pipelines
Governance
microservices
Artificial Intelligence
Requirements Analysis
PySpark
Anomaly Detection
Amazon Web Services
Risk Analysis
Architecture
Safety Principles
Technology Roadmaps
Application Programming Interfaces (APIs)
Communication Skills
Python (Programming Language)
Knowledge of Finance
Amazon S3
SQL Databases
Cloud Services
Data Lakes
Banking Services
Machine Learning Operations
Data Streaming
Technical Management
Technology Strategies
Kinesiology
Apache Hadoop
Governance Risk Management and Compliance
Monitoring of Systems
Event Driven Architecture
Fintech
Debits and Credits
Behavioral Targeting
Feature Engineering
Fraud Prevention and Detection
Google Wallet
Processing of Payments
Risk Measure

Summary

Senior Big Data Engineer AI/ML and Fraud Strategy

Location

Hybrid: 3 days onsite
Approved locations: Pennsylvania, North Carolina, Texas, or Arizona
Contract-to-hire

Position Summary

We are looking for a Senior Big Data Engineer to support the future growth of the client's fraud prevention platform.

The client is expanding into new financial products, including a debit card offering. This role will help define the technology strategy, data architecture, and AI/ML capabilities needed to support new fraud risks and payment-related use cases.

Responsibilities

Define the technology roadmap for the fraud prevention platform.
Design scalable big data and cloud solutions.
Build data pipelines for transaction, customer, payment, and behavioral data.
Support real-time and batch fraud detection.
Apply AI and machine learning for fraud detection, risk scoring, and anomaly detection.
Work with fraud, risk, product, engineering, and business teams.
Support the launch of the new debit card product.
Evaluate payment-processing and financial-partner integrations.
Develop AWS-based data and analytics solutions.
Recommend architecture and technology best practices.
Create technical designs, roadmaps, and solution documentation.
Provide technical leadership and guidance to engineering teams.

Required Skills

Strong big data engineering or data architecture experience.
Strong experience in banking, payments, fintech, or financial services.
Experience with Python, SQL, PySpark, or similar technologies.
Experience with AI and machine learning solutions.
Strong AWS cloud experience.
Experience with Spark, Databricks, Kafka, Hadoop, or similar platforms.
Experience with real-time or streaming data processing.
Knowledge of data lakes, data warehouses, and lakehouse architecture.
Experience with APIs, microservices, and event-driven systems.
Strong understanding of data quality, governance, security, and lineage.
Strong communication and technical leadership skills.

Preferred Skills

Fraud prevention or transaction-monitoring experience.
Debit card, credit card, ACH, digital wallet, or payment-processing experience.
Experience with AWS services such as S3, Glue, Lambda, Kinesis, SageMaker, Redshift, EMR, or Step Functions.
Experience with MLOps, model monitoring, feature engineering, or model governance.
Experience working with payment processors, banks, card networks, or fintech partners.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91134888
Position Id: 2026-3061
Posted 6 hours ago

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