Data Platform Engineer

One’s mission is simple - to help customers achieve financial progress. We’re doing this by creating simple solutions to help our customers save, spend, borrow, and grow their money – all in one place.

The U.S. consumer today deserves better. Millions of Americans today can’t access credit, build savings or wealth, and are left to manage their financial lives through multiple disconnected apps. Almost a quarter of U.S. adults are unbanked or underbanked and roughly 80% of fintech users rely on multiple accounts to manage their finances.

What makes us unique? We are backed by a preeminent fintech investor (Ribbit) and the world’s largest retailer (Walmart), maintain the speed and independence of a startup, and employ a strong (and growing) collection of world-class talent.

There’s never been a better moment to build a business that helps people achieve financial progress. Come build with us!

We are seeking a skilled and experienced Data Platform Engineer to join our growing team. You will be responsible for designing, developing and maintaining our data infrastructure, including data pipelines and data warehouses. This role will play a pivotal part in driving our data strategy, enabling advanced analytics, and supporting Machine Learning operations at scale. You will work closely with the data science, analytics and backend engineering team(s) to ensure our data architecture meets the needs of our business and enables us to make data-driven decisions.

Responsibilities:

• Design, implement, and maintain robust streaming and batch data pipelines using Databricks, Spark, and Python.

• Ensure data infrastructure is reliable, secure, and scalable, adhering to industry regulations and data governance standards.

• Monitor, troubleshoot, and proactively improve data infrastructure to ensure high availability and performance.

• Build and optimize data platforms and warehouses to meet the evolving needs of stakeholders across analytics, machine learning, and backend systems.

• Assist in the re-architecture of batch pipelines to streaming pipelines, ensuring real-time data flow for ML and operational needs.

• Collaborate with data scientists and analysts to streamline data processing for advanced analytics and machine learning.

• Establish and maintain MLOps workflows, ensuring seamless deployment, monitoring, and serving of ML models and features.

• Drive feature engineering and create systems to stage and serve features for machine learning.

• 5+ years of experience in data engineering or a similar role.

• Expertise in Apache Spark for large-scale data processing.

• Advanced knowledge of production-level Python

• Strong SQL skills for data manipulation and ETL processes.

• Experience with real-time streaming technologies such as Kafka or Kinesis.

• Familiarity with MLOps practices and workflows, including feature engineering, model training, and serving.

• Preferred: Proficiency in Databricks for managing data pipelines and analytics workflows, Infrastructure as Code (IaC), Terraform or AWS preferred

• Strong problem-solving skills and the ability to work collaboratively in cross-functional teams.

• An “act-like-an-owner” mentality with a bias toward taking action.

We use Covey as part of our hiring process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on May 31, 2024.

Please see the independent bias audit report covering our use of Covey here.

In order to thoughtfully scale the company and avoid downstream inequities, we’ve adopted a flat titling structure at One. Though we may occasionally post a role externally with a prefix such as “Senior” to reflect the external level of the position, we do not use prefixes in titles like that internally unless in a position which manages a team. Internal titles typically include your specific functional responsibility, such as engineering, product management or sales, and often include additional descriptors to ensure clarity of role and placement within our organization (i.e. “Engineer, Platform”, “Sales, Business Development” or “Manager, Talent”). Employees are paid commensurate with their experience and the internal level within One.

To build technology and products that are used and loved by people and solve real-world problems, we need to build a team with many different perspectives and experiences. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We encourage candidates from all backgrounds to apply. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us at [email protected].