Big Data Engineer - AI/ML and Fraud Strategy

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.