Data and Operations Engineer Staff Principal Lead

Sadient•San Francisco, CA

5d•$300,000 - $380,000•Onsite

About The Position

The Client is building a global consumer neobank, merging banking, payments, and crypto into a single product. Their initial focus is on emerging markets where traditional banking and local currencies fail hundreds of millions of people. They aim to enable users worldwide to move their money seamlessly within their ecosystem. The company is built by experienced operators and engineers, forming a small, senior-only team without layers, politics, or slow decision-making. They have a track record of building and owning services used by hundreds of millions of people, generating billions in revenue. This role is a key part of their next venture, with mass distribution readily available through day-one partners. Every team member ships product and shapes the company's direction. As a founding Data and Operations Engineer, you will define and work on core systems and workflows that feed data across the internal architecture and beyond. Your architecture and processes will be crucial for enabling engineers to aggregate critical product data and platform telemetry into a unified analytics platform, allowing the FinOps team to ensure consistent, reliable ledgers, and empowering the Fraud AML team to build high-quality risk models by shipping clean, understandable data models.

Requirements

Extensive hands-on experience building scalable data architectures in a consumer-oriented FinTech environment using Terraform, dbt, and SQL.
Expert-level knowledge of data-centric development patterns for writing and validating various flavors of code deployed across internal and hosted environments.
Fluent technical communication, especially written, for AI and non-SME consumption.
Python

Nice To Haves

Data visualization and storytelling techniques.
Deep expertise with full-stack applications.
Machine learning.
Specific experience with global payments, ledgering, and other user-facing FinTech applications.

Responsibilities

Define and work on the core systems and workflows that feed data across the internal architecture and beyond.
Allow fellow engineers to aggregate critical product data and platform telemetry into a unified analytics platform.
Enable the FinOps team to ensure consistent, reliable ledgers across financial partners and accounts.
Empower the Fraud AML Anti Money Laundering team to build high-quality risk models and workflows by shipping clean, understandable data models into the internal decisioning platform.
Use expert knowledge in Terraform, dbt, and AWS products to ensure data and applications are built on a solid, robust foundation.
Define safe and secure Least Access patterns that allow man and machine alike to get the data they need when they need it, preserving data lineage and ensuring data governance as part of the regulatory and compliance ecosystem.
Document and educate the rest of the engineering team in the care and feeding of high-quality infrastructure systems that will support the global user base.