Descripción de la oferta
Responsibilities
Senior Staff Data Engineer to be the technical leader of our Data Engineering group within the SoFi Data Platform (SDP) division
Activate data throughout SoFi, enabling the creation of personalized and delightful experiences for our members
Directly impact, influence and lead the direction and architecture of our next‑gen AI powered SDP, and elevate data reliability through AI enabled workflows, tooling and practices
Lead, define, and take on complex and interesting problems as part of a fast‑paced, highly collaborative organization
Provide primary technical authority and strategic guidance to the data engineering group (Technical Leadership & Strategy)
Lead the architecture and delivery of large‑scale, high‑performance data pipelines and processing frameworks; design scalable data models that support analytics, AI/ML and real‑time data needs (Architectural Excellence)
Drive the adoption of cloud‑native technologies, automation frameworks and reusable components that improve development velocity and system reliability across SDP (Platform Innovation)
Drive org‑wide initiatives to improve data reliability, cost‑efficiency and latency; design solutions that scale horizontally and vertically to handle ever‑growing datasets (System Optimization)
Partner with business stakeholders, product and engineering leads to align the data roadmap with SoFi’s business objectives (Cross‑Functional Collaboration)
Lead the implementation of sophisticated data privacy, security and compliance frameworks; enforce data governance policies and practices to maintain data integrity in a highly regulated environment (Governance & Security)
Provide deep technical coaching and mentorship to Staff and Senior data engineers, fostering a culture of continuous learning, rigorous testing and engineering excellence (Mentorship)
Contribute to hiring and training efforts to build a skilled and motivated data engineering workforce; lead the interview process for senior‑level talent and design onboarding programs that accelerate engineering productivity (Workforce Development)
Be part of an on‑call support rotation to support the critical production systems (On‑Call Support)
Benefits
Generous vacation and holidays
Paid parental leave for eligible employees
401(k) and education on retirement planning
Monthly contribution up to $200 to help you pay off your student loans
Great health & well‑being benefits including telehealth, parental support, and subsidized gym program
Comprehensive health, vision, dental, life insurance, and disability benefits
Fertility and family planning options
Flexible time off
Free financial classes
Tuition reimbursement on approved programs, up to $5,250 per year
Qualifications
The ideal candidate will be a mentor, technical leader and a team player who is hands‑on and comfortable driving solutions from initial architecture to implementation and adoption, with a strong sense of ownership and drive for delivery
Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field (Education)
Expert‑level proficiency in relational and cloud database platforms (Snowflake, Redshift, or GCP) and distributed processing frameworks (Hadoop, Spark, or Kafka) (Cloud Architecture)
Deep experience in a highly regulated and governed sector; experience in the FinTech industry is highly advantageous (Domain Knowledge)
Exceptional ability to communicate complex technical concepts and trade‑offs to non‑technical stakeholders and senior management (Communication)
Over 12 years of experience in data engineering and analytics, with at least 4 years in a staff‑level or higher capacity; a proven track record of successfully leading enterprise‑wide data modernization efforts (Experience)
Mastery of the modern data stack: Snowflake, Python, SQL, GitLab, AWS, Airflow, AI tools like Claude code/Cursor; understanding and implementation experience of AI agents is a plus (Tech Stack Mastery)
Thorough knowledge and passion for data modeling (Kimball/Data Vault), database design and data architecture principles; ability to simplify complex, ambiguous issues into actionable technical plans (Strategic Thinking)
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