Senior Data Analytics Engineer

Summary

Join Marqeta's Risk, Fraud, and Disputes Engineering team as a Senior Data Analytics Engineer. This cross-functional role involves designing and developing scalable data assets for real-time fraud detection, dispute operations, and regulatory reporting. You will bridge data engineering with analytical needs, enabling data-driven decisions through structured data and actionable insights. Partner with various teams to understand business needs and translate them into data solutions. Lead the creation of labeled datasets for machine learning models and create real-time dashboards and reporting. Recommend data improvements and act as a domain expert in fraud and dispute data. Collaborate with engineering to develop and maintain data pipelines. This role offers flexible work arrangements and is remote-friendly within the United States.

Requirements

• 5+ years of experience in data analytics, data science, or data engineering, preferably in fraud, risk, dispute, payments, or financial services
• Advanced SQL skills with a strong understanding of analytical functions, performance tuning, and ETL best practices
• Deep understanding of risk, fraud signals, disputes domain or related data patterns
• Strong data intuition: able to translate vague problem statements into structured data analysis or model features
• Experience with data visualization tools (Looker, Tableau etc)
• Ability to translate business needs into technical solutions and data structures
• Comfort working with ambiguous data problems in a fast-paced, high-stakes environment
• Strong communication and collaboration skills—ability to work cross-functionally with Product, Engineering, and Ops
• Familiarity with Airflow, dbt, or equivalent ETL/ELT tooling

Responsibilities

• Partner with risk/fraud/dispute engineers, data scientists, and product managers to understand business needs and translate them into data-driven solutions
• Lead the creation of labeled datasets to support supervised machine learning and rules-based fraud detection and chargeback prediction
• Partner with ML engineers and backend teams to productionize data
• Analyze large transactional, fraud, and chargeback data to uncover trends, detect anomalies, and support deep-dive investigations.(e.g., Chargeback win/loss rates, Fraud rates, anomalous Merchant behavior etc)
• Create and maintain real-time dashboards and reporting for key KPIs across Fraud, Risk, and Disputes for leadership, operations, and product teams
• Recommend data improvements to enhance fraud and chargeback detection capabilities and reduce false positives/negatives
• Act as a domain expert in fraud and dispute data, supporting internal investigations and external customer data queries
• Partner with Finance or Operations to answer questions about dispute costs, win/loss rates, and more
• Collaborate with Engineering to develop and maintain Airflow pipelines and ETL workflows to support scalable data pipelines

Preferred Qualifications

• Experience labeling data for ML models or partnering with ML engineers on feature creation
• Understanding of card network chargeback rules, fraud reason codes, or dispute lifecycle
• Python or R for advanced analytics or light ML tasks

Benefits

• Multiple health insurance options
• Flexible time off – take what you need
• Retirement savings program with company contribution and after tax contributions
• Equity in a publicly-traded company and an Employee Stock Purchase Program
• Family-forming benefits, fertility support, and up to 20 weeks of Parental Leave
• Free therapy sessions, financial and professional coaching, and legal advice
• Monthly stipend to support our remote work model
• Annual “development dollars” to support our people growth and development