Senior Manager, Data Engineering
MoneyLion
Gen is a global company dedicated to powering Digital Freedom through its trusted consumer brands including Norton, Avast, LifeLock, MoneyLion and more. Our combined heritage is rooted in financial empowerment and cyber safety for the first digital generations, and today we deliver award-winning cybersecurity, online privacy, identity protection and financial wellness solutions to nearly 500 million users in more than 150 countries.
Together, we share a collective passion and vision to protect consumers and help them grow, manage and secure their digital and financial lives. We’re always looking for smart, fearless and high-impact talent who see AI as a teammate – leveraging it to move faster and deliver meaningful results.
When you’re part of Gen, you’ll have the flexibility, tools and support to do your best work and grow your career – from flexible working options and time off to competitive pay, benefits and well-being programs.
At Gen, we are scrappy and relentlessly customer driven. We create room for healthy debate, experimentation and continuous learning, and we seek out people with different experiences, identities and ideas to join our team. You’ll work with people who back each other, respect each other and understand that our differences are a competitive advantage.
If this sounds like you, we’d love you to be part of Gen.
About the RoleWe are seeking an experienced Senior Manager, Data Engineering to serve as a technical people leader responsible for owning the deliverables of your team and going the distance to empower them to achieve their objectives. You can expect to be architecting systems within your team's domain and driving complex, cross-team projects that directly support our cybersecurity platform's strategic objectives. This role requires someone who can architect systems within your team's domain, reasonably be expected to come up with and drive the projects that your crew should do to solve complex business problems.
As a Senior Manager, Data Engineering, you are expected to manage your time between Individual Contributor (IC) hands-on-keyboard coding, PR reviewing and managing your team across its entire domain. You are expected to participate, contribute and improve the hiring process and be an active champion of the org’s cross-geographical RFC & Technical Specification review process.
Above all, you will be an authority on crafting thoughtful solutions that will empower absolutely everyone at Gen Digital towards an agentic AI-first analytics and development lifecycle.
Key Responsibilities- Own the people management responsibilities of a team of driven Data Engineers – including performance & compensation management, hiring and mentorship.
- Extensive expertise operating & optimizing a modern data warehousing solution (Snowflake preferred) from both performance and cost perspectives.
- Expertise with Apache Kafka, real-time data processing, and event-driven architectures
- Experience with Apache Iceberg, data lakehouse architectures, and modern table formats
- Design and architect enterprise-scale data solutions that directly impact Gen's data strategy execution. Contribute a minimum of 1 exemplary technical spec per year that massively moves Gen’s data architecture forward.
- Lead evaluation and implementation of cutting-edge technologies including modern data stack and advanced analytics
- Collaborate with executives and senior leadership to align data architecture with business strategy and manage senior stakeholders from external departments
- Drive complex, multi-quarter technical initiatives requiring coordination across multiple engineering teams
- Bachelor's degree in computer science, Data Engineering, or related technical field
- 5-10 years of hands-on data engineering experience in large-scale, high-volume environments, with 1-2 years of management experience
- Expert-level proficiency in SQL optimization for multi-petabyte datasets and advanced Python programming
- Extensive experience with Snowflake architecture, optimization, and cost management at enterprise scale
- Demonstrated expertise building Kimball dimensional data warehouses and star schema architectures
- Advanced experience with AWS cloud infrastructure and either DBT or SQLMesh for data transformations
- Hands-on experience with CI/CD pipelines, GitFlow, and data governance frameworks ensuring GDPR/PCI-DSS compliance
- Familiarity with AWS is a big plus
- Experience in planning day to day tasks, knowing how and what to prioritise and overseeing their execution
- Experience working with PMO, other data specialities (analysts, scientists, machine learning), and working across time zones.
- TA Call
- Technical Screening - PR Review Exercise
- Technical Screening - Focused on Snowflake and Dimensional Modeling
- Hiring Manager Interview - Whiteboarding Design Round
- Bar Raiser Round
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