
DI Team Lead
New York, NY · HybridFull-time$165–175K/yrPosted todayStill listed today
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At a glance
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Job overview
Riskified is seeking a leader for its Data Integration Engineers, who advise retail clients and support integrations that improve ecommerce conversion and reduce fraud. The role manages a distributed team, guides complex integration work, and partners across Operations, Sales, Product, Development and Data Science. It also helps shape shared tools, processes and automation, including AI-driven workflows, to improve onboarding speed and integration quality.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
About Us
Riskified empowers businesses to unleash ecommerce growth by taking risk off the table. Many of the world’s biggest brands and publicly traded companies selling online rely on Riskified for guaranteed protection against chargebacks, to fight fraud and policy abuse at scale, and to improve customer retention. Developed and managed by the largest team of ecommerce risk analysts, data scientists and researchers, Riskified’s AI-powered fraud and risk intelligence platform analyzes the individual behind each interaction to provide real-time decisions and robust identity-based insights. Riskified is proud to work with incredible companies in virtually all industries including Acer, Gucci, Lorna Jane, GoPro, and many more.
We thrive in a collaborative work setting, alongside great people, to build and enhance products that matter. Abundant opportunities to create and contribute provide us with a sense of purpose that extends beyond ourselves, leaving a lasting impact. These sentiments capture why we choose Riskified every day.
About the Role
Riskified’s clients span many sizes and software platforms, and each comes with its own business and data flow requirements. Our Data Integration Engineers act as trusted technical advisors, helping brand-name retailers integrate with Riskified to improve their eCommerce conversion rate and reduce online fraud. The team ensures data quality, validates data flows and supports clients throughout integration and beyond, from designing customized flows to building tools that automate data validation.
We’re looking for an experienced, technical and business-savvy leader to head our team of Data Integration Engineers. You will develop and guide the team, and work closely with Operations, Sales, Product, Development and Data Science as an advocate for our clients. Together with DI leadership across regions, you will help shape the tools and ways of working that will enable us to scale, including the adoption of AI.
What You’ll Be Doing
Lead the team
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Manage, coach and develop a distributed team of 5 Data Integration Engineers across the U.S. East Coast and Brazil, with a focus on technical excellence and a great client experience
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Set and balance the team’s priorities across client commitments, SLAs and business goals
Oversee and support integrations
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Guide the team through non-standard integration challenges, from designing the right endpoints and data flows for merchants with unique setups to finding ways to automate, limit or eliminate manual work
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Serve as an escalation point for the team
Strengthen how DI works
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Take an active part in shaping and implementing shared tools, processes and automation across the global DI team, including AI-driven workflows such as automated data validation
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Help continuously improve merchant onboarding, in both speed and integration quality
Qualifications
Candidates must be currently authorized to work in the United States on a full-time basis without the need for employer visa sponsorship.
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4+ years of experience as a leader of data integrations / data solutions / software engineering teams with a focus on data management
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6+ years of experience in professional services / software / data engineering roles
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3+ years of hands-on experience with SQL, Python or other data engineering programming languages
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Experience working with data lakes and data warehouses
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Experience with data quality assurance and control (QA/QC), such as defining validation checks and monitoring data integrity
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Experience working with SaaS solutions and APIs
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Hands-on experience bringing AI into team operations, such as using LLMs to automate data validation, speed up client onboarding or streamline integration workflows
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Proven ability to handle multiple projects with competing priorities
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Comfortable working in a fast-paced environment with high-stakes client timelines
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Excellent written and verbal communication skills
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Understanding of Machine Learning and Data Science is a plus
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E-commerce or Payments industry experience is an advantage
The base salary range for this position is $165,000 - $175,000. This range is applicable to candidates who will perform the job either wholly, or in part, within New York City. Actual salary will be based on qualifications, competencies, and location. If you feel this range is not attractive, we encourage you to let us know through the application process.
Base salary is just one part of the pay package at Riskified. All full-time regular employees receive a bonus target and are eligible to receive stock-based awards. Also, our value proposition goes way beyond compensation: our perks and benefits package, culture, community, and learning and development programs are just some of the elements we provide to bring value to our employees. We invite you to apply at www.riskified.com to learn more about what we have to offer.
Life at Riskified
We are a fast-growing and dynamic tech company with 750+ team members globally. We value collaboration and innovative thinking. We’re looking for bright, driven, and passionate people to grow with us.
Some of our NYC Benefits & Perks:
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Our NYC team is currently working in a hybrid of remote and in-office for all our team members
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Fully-covered medical, dental, and vision insurance from your first day
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Equity for all employees, 401(k) + matching, commuter benefits
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Catered lunch, fully-stocked kitchen, team events, happy hours, birthday celebrations
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Yoga, pilates, soccer league, wellness classes
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Wide-ranging opportunities to volunteer and make an impact in local communities
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Commitment to your professional development with global onboarding, sales bootcamp, skills-based courses, full access to Udemy, lunch & learns
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Awesome Riskified gifts and swag!
In the News
Reuters: General Atlantic-backed Riskified valued at $4.3 bln in NYSE debut
Fortune Magazine: Riskified named Best Workplaces in New York for 2022
The Muse: Q&A with Sales Enablement Manager Benedikt Parstorfer
Globes: Riskified is among Israel’s fastest growing companies
TechCrunch: Riskified Prevents Fraud on Your Favorite E-commerce Site
CTech: Riskified’s VP HR on Post-COVID Flexible Work Routines
Riskified is deeply committed to the principle of equal opportunity for all individuals. We do not discriminate based on race, color, religion, sex, sexual orientation, national origin, age, disability, veteran status, or any other status protected by law.
How this job compares
Set against the 1,182 open Software Engineering Manager jobs on Olive Jobs, counted November 6, 2026.
- Pay
- This posting$165–175K/yr
- New York median$171–262K/yr59 salary ranges
- US median$143–262K/yr1,003 salary ranges
This range's midpoint, $170K, is 20% below the New York median midpoint ($213K) — in the middle half of Software Engineering Manager salary ranges in New York.
- Openings
- Olive Jobs lists 66 open Software Engineering Manager jobs in New York and 1,182 across the US. 5% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 6 years of experience; Software Engineering Manager postings that state a minimum ask for 8 years at the median (1,077 postings).
- Education
- 421 of the 1,182 open Software Engineering Manager jobs (36%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 6, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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