&lt;p&gt;Marqeta is on a mission to change the way money moves. Our open API card issuing platform provides unprecedented flexibility and control for industry-leading companies such as Square, Coinbase, J.P.Morgan, and Uber, to issue cards, authorize transactions, and manage payment operations in real time. Founded in 2010, Marqeta IPO’d in 2021 and has grown into a team of over 900 Marqetans in the US, UK, Canada, Singapore, and Australia.&amp;nbsp;&lt;/p&gt;
&lt;p&gt;The Data team is responsible for developing big data-related technology/services and value-added data products. Our technologies include large-scale, reliable, and secure Data platforms in the cloud for data acquisition, processing, enriching, serving, consumption, and governance. We invest in ML/AI and ML/AI applications (e.g. fraud risk detection and management), data processing, analytics technology, and products to derive deep and actionable insights and values from data to empower Marqeta internal teams and external customers to grow faster and more effectively.&lt;/p&gt;
&lt;p&gt;As Marqeta’s Engineering VP, reporting to the SVP of Data, you will own the areas of data processing, services, analysis, ML/AI model development and application, payment/finance data reconciliation, and value-added data products. You will influence and contribute to our vision, direction, and strategy. You will lead teams to develop our scalable platforms and solutions covering Data as a Service, Insights as a Service, Recon product, ML/AI technology &amp;amp; applications, as well as find effective ways to empower internal and external partners/customers to generate business values.&amp;nbsp;&lt;/p&gt;
&lt;p&gt;We work &lt;a href=&quot;https://www.marqeta.com/blog/2022/05/10/flexible-first&quot;&gt;Flexible First&lt;/a&gt;. This role can be performed remotely anywhere within the U.S.&amp;nbsp; or from our local Oakland office. We’d love for you to join us!&lt;strong&gt; &lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;What You’ll Do&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Provide organizational and technical leadership across the areas of data processing &amp;amp; serving system development, data analysis, metrics definition and development, modeling using techniques like ML/AI for solving all kinds of business problems like fraud risk, recon, and value-added data products.&lt;/li&gt;
&lt;li&gt;Partner with technical leaders to champion and evangelize the architectural vision for an organization driving continuous delivery that provides measurable value to customers.&lt;/li&gt;
&lt;li&gt;Develop a strategy, and roadmap to meet business objectives with existing or emerging technologies related to big data, insights, and value-added data products.&lt;/li&gt;
&lt;li&gt;Scale Marqeta’s data, data platform, data processing, serving, data analysis, data modeling, and value-added product systems to support multiple orders of magnitude transactional growth, while at the same time reducing human and infrastructure costs to support.&lt;/li&gt;
&lt;li&gt;Develop testable, observable, scalable, trustworthy systems using rigorous agile methodology and analysis/engineering best practice including eliminating manual tasks from the financial industry.&lt;/li&gt;
&lt;li&gt;Lead and collaborate with engineering teams on assignment management, hiring, mentorship, and performance management.&amp;nbsp;&amp;nbsp;&lt;/li&gt;
&lt;li&gt;Work with the Product Management team to deliver data processing &amp;amp; serving systems, data analysis, effective metrics/reporting, effective advanced models for solving customer &amp;amp; Marqeta business problems.&amp;nbsp;&lt;/li&gt;
&lt;li&gt;Drive an engineering culture that cares about customer engagement, team velocity, quality, trust, team building, and recruiting.&lt;/li&gt;
&lt;li&gt;Drive Security/Privacy, Quality, Reliability, Usability, Scalability/Performance, Productivity/Efficiency, and Operability through our systems/products/services and into the DNA of the organization overall.&lt;/li&gt;
&lt;li&gt;Foster learning, innovation, leveraging and building on new technologies.&lt;/li&gt;
&lt;li&gt;Define success metrics, SLAs and track them toward agreed targets.&lt;/li&gt;
&lt;li&gt;Operational Excellence: guide teams monitoring &amp;amp; operating production services, including understanding user experience and ensuring happy customers.&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;What We’re Looking For&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Bachelor&#39;s degree in a technical field such as computer science, engineering, or equivalent years of experience.&amp;nbsp;&lt;/li&gt;
&lt;li&gt;You have 15+ years of industry experience in big data, large-scale data platforms, and data analysis/science including ML/AI, and value-added data products.&lt;/li&gt;
&lt;li&gt;5 years of recent experience managing data science and engineering teams in the Big Data, data analysis, and ML areas.&amp;nbsp;&lt;/li&gt;
&lt;li&gt;You demonstrate strong leadership, self-motivation, accountability, and can represent the Data organization, both on the technical and business side.&lt;/li&gt;
&lt;li&gt;Familiarity with cloud technology and commonly used open-source packages - Spark, HBase, Kafka, Kubernetes, and ML/AI packages.&amp;nbsp;&lt;/li&gt;
&lt;li&gt;A customer-centric mindset, measuring and monitoring service from a user’s angle.&amp;nbsp;&lt;/li&gt;
&lt;li&gt;Ability to establish credibility, build rapport and influence senior leaders, including Product and Engineering teams.&lt;/li&gt;
&lt;li&gt;Operational Rigor and thoughtfulness in addressing the root cause of systemic issues rather than treating symptoms in data management, data analysis, data processing, data serving, query processing, distributed processing, high availability, statistics, data mining, machine learning, AI, and production systems.&lt;/li&gt;
&lt;li&gt;Data-driven - defining and delivering KPI&#39;s for quality and productivity with automated mechanisms for transparency and visibility.&lt;/li&gt;
&lt;li&gt;Track record of attracting, developing, and building high-performing engineers/data scientists.&lt;/li&gt;
&lt;li&gt;Intellectually honest - balanced view on your own capabilities and where to augment gaps with strong talent.&lt;/li&gt;
&lt;li&gt;Simple and scalable - you thrive on creating simple elegant solutions that scale and reduce complexity, including removing code to keep human toil/support to a minimum.&lt;/li&gt;
&lt;li&gt;Ability to build engineering and data analysis plans, and strategy, through documentation and presentations to internal stakeholders and customers.&amp;nbsp;&lt;/li&gt;
&lt;li&gt;Deep experience with the software development lifecycle using agile methodologies.&lt;/li&gt;
&lt;li&gt;Ability to work well in a cross-functional, matrix management environment.&lt;/li&gt;
&lt;li&gt;You effectively communicate with different audiences, both internal and external customers, from engineers to CEOs.&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Nice-To-Haves&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Masters degree&lt;/li&gt;
&lt;li&gt;Experience in large-scale ML/AI model development or ML/AI platform development is a plus.&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Your Manager&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;&lt;a href=&quot;https://www.linkedin.com/in/zijianzheng/&quot;&gt;Zijian Zheng&lt;/a&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Recruiter For This Role&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;&lt;a href=&quot;https://www.linkedin.com/in/patti-g-lopez-6b391a1/&quot;&gt;Patti Lopez&lt;/a&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Typical Process&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Application submission&lt;/li&gt;
&lt;li&gt;Recruiter phone call&lt;/li&gt;
&lt;li&gt;Hiring manager video call&lt;/li&gt;
&lt;li&gt;Virtual “Onsite” consisting of 5-6, 45 min calls&lt;/li&gt;
&lt;li&gt;Offer!&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Compensation and Benefits&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Flexible time off – take what you need&lt;/li&gt;
&lt;li&gt;Retirement savings program with company contribution&lt;/li&gt;
&lt;li&gt;Equity in a publicly traded company and an Employee Stock Purchase Program&lt;/li&gt;
&lt;li&gt;Health insurance premiums paid 100% + coverage for dependents and pets&lt;/li&gt;
&lt;li&gt;Family-forming benefits, fertility support, and up to 20 weeks of Parental Leave&lt;/li&gt;
&lt;li&gt;Free therapy sessions, financial coaching, and legal advice&lt;/li&gt;
&lt;li&gt;Monthly stipend to support our remote work model (&lt;em&gt;#LI-Remote&lt;/em&gt;)&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;&lt;strong&gt;Visa Sponsorship&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;We do not currently support any new sponsorship opportunities or sponsorship transfers for this role&lt;/li&gt;
&lt;/ul&gt;&lt;div class=&quot;content-conclusion&quot;&gt;&lt;p&gt;&lt;span style=&quot;font-weight: 400;&quot;&gt;Our &lt;/span&gt;&lt;a href=&quot;https://www.marqeta.com/company/applicant&quot;&gt;&lt;span style=&quot;font-weight: 400;&quot;&gt;Applicant and Candidate Privacy Notice&lt;/span&gt;&lt;/a&gt;&lt;span style=&quot;font-weight: 400;&quot;&gt; applies to the personal data that you directly provide to us or that we collect during the application and candidate recruitment process.&lt;/span&gt;&lt;/p&gt;
&lt;h6 style=&quot;text-align: right;&quot;&gt;&amp;nbsp;&lt;/h6&gt;&lt;/div&gt;

Data

Remote, USA

Engineering VP, DS, ML/AI, and Data Products

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