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Splash Financial

Remote Principal Data Engineer

1w

Splash Financial

Cleveland, US · Full-time · $220,000 – $235,000

About this role

Splash Financial seeks a highly skilled Principal Data Engineer to design and implement a scalable, reliable, high-performance data platform. You will develop data models, architect robust big data systems, and ensure scalability and fault tolerance across the data ecosystem. This role demands a strong background in data engineering, distributed systems, and cloud infrastructure.

Day-to-day involves designing end-to-end big data solutions meeting functional and non-functional requirements with focus on scalability, reliability, and performance. You will create logical and physical data models for structured, semi-structured, and unstructured data while optimizing storage and processing layers for performance and cost-efficiency. Collaboration with engineering, data science, product, and infrastructure teams ensures seamless data flow and interoperability.

Splash is remote-first and proud of it, operating like a fast-paced, nimble startup full of heart since 2013. Work is guided by values like Own It, Raise the Bar, Say the Hard Thing, and Elevate Each Other, fostering creativity, passion, and urgency. Teams connect through Slack channels for #kids-and-pets and #food, blending professional and human moments.

Join a Cleveland-born company that has refinanced $6+ billion in loans and raised over $135 million from top investors to empower people beyond their debt. Focus on building financial technologies that transform lending through marketplace and automated loan processing. We're just getting started on making a splash in the world.

Requirements

  • Strong background in data engineering
  • Experience with distributed systems
  • Knowledge of cloud infrastructure
  • Deep understanding of best practices in data modeling
  • Expertise in system architecture
  • Proficiency in data governance
  • Ability to design scalable, high-performance data platforms

Responsibilities

  • Design and implement end-to-end big data solutions focusing on scalability, reliability, and performance
  • Design logical and physical data models for structured, semi-structured, and unstructured data
  • Work closely with engineering, data science, product, and infrastructure teams for seamless data flow and system interoperability
  • Optimize storage and processing layers for performance and cost-efficiency
  • Ensure high availability and disaster recovery for the data platform
  • Establish data governance standards including data quality, metadata management, and lineage tracking
  • Architect robust big data systems ensuring fault tolerance across the data ecosystem

Benefits

  • Remote-first workplace
  • Great health insurance
  • Quarterly meet-ups
  • Access to engagement tools that keep us connected
  • Slack channels for #kids-and-pets and #food