Data & Intelligence Platform Lead

Summer

5h•$200 - $200•Remote

About The Position

We are seeking a Data & Intelligence Platform Lead to join our Engineering team. In this role, you will be the foundational architect of Summer’s Data & Intelligence Platform. You will lead evolution from an application-first data culture—currently reliant on tribal knowledge and an ad hoc data lake—to an enterprise-grade platform capable of powering strategic business insights and AI-driven debt optimization at massive scale. You will architect the "Identity" strategy that stitches together disparate federal and private data sources into a definitive user profile, ensuring Summer is Data Centric, AI-Native, and strategically prepared to navigate the complex business landscape intrinsic to the student loan ecosystem. You will also support the business as a whole, including preparing data artifacts, processes, and governance methodologies to enable Sales, Marketing, Operations, and the entire Summer team.

Requirements

The Foundation: 8+ years of experience in Data Engineering or Platform Architecture, ideally within high-growth Fintech or highly regulated environments.
Architectural Vision: Proven track record of moving an organization from ad-hoc reporting to a structured "Data Platform" mindset.
AI/ML Fluency: Deep experience with the data-side of LLM orchestration, including RAG architectures, Vector Databases (Pinecone, Weaviated), feature stores, and more.
Technical Mastery: Expert knowledge of Snowflake, Python, dbt, and Airflow. Experience with Kubernetes-based data stacks and other ETL/reverse-ETL tools.
Systems Thinker: You don't just solve tickets; you solve bottlenecks. You think in terms of feedback loops, unit economics, and scalable patterns.
B-Corp Spirit: A commitment to using data as a force for good. You believe clean data is a prerequisite for financial justice.

Responsibilities

Full enterprise data management: Define and execute the strategy for end-to-end data lifecycle management, including ingestion, storage, processing, quality, and accessibility, establishing data as a first-class, reliable asset across all business functions.
Borrower Identity Architecture: Lead the "stitching" of disparate data sources (federal servicers, payroll, and private lenders) to create a high-fidelity, 360-degree view of a user’s debt history.
Mature the Data Lake: Mature our current Snowflake infrastructure into a governed, high-performance BI layer. You will eliminate "tribal knowledge" by codifying naming conventions and logic into clean, reusable models.
AI-Native Core: Build and maintain the "Feature Store" and semantic layer required for possible AI features including agentic policy decoding, workflow review anomaly detection, and more.
Contextual Reasoning: Implement the data structures (Vector stores, Graph-based logic) that allow AI agents to navigate complex regulatory relationships on behalf of our rapidly growing user base.
Feedback Loops: Orchestrate data pipelines to ensure model predictions and behavioral signals flow back into the product UI, creating a virtuous cycle of user value.
Self-Service Sovereignty: Partner with our Analytics team to minimize ad-hoc data requests. You will build the frameworks that allow analysts to self-serve without reinventing logic.
Observability by Default: Partner with our application teams to ensure that every new feature is instrumented for deep product analytics, system health, and data mining from day one.
Cross-Functional Synergy: Bridge the gap between engineering and product / analytics, ensuring our technical architecture seamlessly supports the product and business needs before we have them.
Security: Ensure the absolute protection of user PII and financial data and partner information, upholding the core mandate of security.
Compliance: Implement and maintain industry-leading frameworks (e.g., SOC 2 Type II, FedRAMP) to meet the highest security standards for partner and government due diligence.
Ethical and Fair Practices: Establish and enforce ethical guidelines for data collection, storage, and AI model usage (e.g., fairness, bias detection, and transparency) to ensure all decisions fairly serve the financial well-being of our users, aligning with our B-Corp mission for financial justice.
Data Stewardship & Ownership: Implement automated data discovery, classification, and lineage tools to codify data ownership, establish clear metadata processes, and ensure data is well-understood and governed across the entire organization.