Senior Data Analytics Engineer – Risk, Fraud and Disputes

About the Role

We are looking for a highly analytical and technically proficient Senior Data Analytics Engineer to join our Risk, Fraud, and Disputes Engineering team. In this cross-functional and strategic role, you’ll own the design and development of scalable, reliable data assets that drive real-time fraud detection, dispute operations, and regulatory reporting. You'll be instrumental in bridging data engineering with analytical needs, enabling high-quality decisions through structured, labeled data and actionable insights using ML models.

We work Flexible First. This role can be performed remotely anywhere within the United States. We’d love for you to join us!

The Impact You'll Have

• 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.

Who You Are

• 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.

Nice-To-Haves

• 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.

Compensation and Benefits

Marqeta is a Flex First company which allows you to choose your best working environment, whether that be from home or at a company office. To support Flex First, we calibrate pay to a competitive value according to working location. Compensation is aligned according to three tiers within the United States:

• National: A baseline tier that applies to most of the geographic territory of the United States.
• Premium: Slightly elevated from the National tier, and oriented toward a narrower set of higher cost-of-living areas, such as Los Angeles CA and Seattle WA
• Premium Plus: A tier for the most expensive working areas, like the San Francisco Bay area and New York City.

Visit this page or consult with a Recruiter to determine which tier would be applicable to you.

When determining salaries, we consider several factors including, but not limited to, skills, prior experience, and work location. The new-hire base salary range for this position is:

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