Data Engineer

K-Dimensional Holdings Inc.•New York, NY

72d•$130,000 - $160,000•Onsite

About The Position

Coast is re-imagining the trillion-dollar U.S. B2B card payments infrastructure, with a focus on the country's 500,000 commercial fleets, 40 million commercial vehicles, and many million commercial drivers. The incumbent technologies that cater to these customers are decades old, and drivers, fleets, and the merchants that serve them all increasingly demand modern digital experiences and affordable and transparent financial services products. Coast's mission is to deliver them at a transformational scale, and to improve working lives in one of the country's biggest industry sectors. The company is backed by top fintech and mobility venture funds. In order to maximize our engineering velocity, we are hiring in NYC and the tri-state area only. Our office is located in the heart of Manhattan's SoHo neighborhood, benefiting from its vibrant creative energy. We come to the office on average four days a week. At Coast, the success of our data platform is driving accelerating demand from all corners of the company. We're looking for a key builder to help us meet this moment. In this role, you will drive the delivery of high-impact analytics and AI use cases while contributing to the evolution of our modern, cloud-native data platform. This is a chance to join a small, high-leverage team and make a definitive impact, building the systems that help us understand risk, acquire customers, and create a better financial product. You will be building on a solid foundation that lets you focus on high-impact work from day one. Our data engineering organization follows the federated model of data product ownership-the data platform serves as the foundation, not the first line of defense against data issues. This role is a launchpad for the next step in your career. You'll partner directly with business leaders and have outsized ownership, helping to steer the company's direction. This role reports to the Lead Data Engineer that heads up our Data organization.

Requirements

Professional experience: 4+ years working with SQL, Python, data pipelines, and BI tools.
Strong Python & software engineering mindset: you are a proficient Python developer who leads with principles of source control, infrastructure as code, testing, and automation. This is more important to us than deep expertise in any single data tool.
Robust, production-grade data pipeline designer: you understand the importance of testing and validation, you have tools in your toolbelt to deal with data from a variety of sources (APIs, GraphQL, Salesforce), optimize transformations and produce consumer-ready datasets.
Orchestration experience: you have hands-on experience with a modern data orchestrator. Direct experience with Dagster is a huge plus, but experience with tools like Airflow, Prefect, or other code-first orchestration tools is also highly valuable.
Pragmatic problem-solving: you can figure things out. You're comfortable researching a problem, designing a solution, implementing a technical spike, and then delivering it through responsible change management. You have the bias for action.
Solid data fundamentals: you have a solid grasp of SQL and data modeling principles. You don't need to be a world-class SQL optimizer, but you understand how to build clean, reliable datasets.
An owner's mindset: you are proactive and take ownership of your work from end to end. You treat the platform as your product.

Responsibilities

Own the delivery of data: you will design and deliver data for a variety of use cases from all areas of the business (marketing & sales, growth, risk, compliance, product, etc.) with robustness and high degree of automation.
Orchestration: you'll design, build, and maintain robust, scalable, and testable data assets using Dagster.
Build Data Products & Pipelines: you'll implement and deploy new ELT pipelines and data transformations using our modern SQL-based stack (dbt, Redshift, Python) to support critical business use cases.
Apply Software Engineering Principles: you'll champion and apply software engineering best practices-including robust testing, CI/CD, modularity, and observability-to every part of our data platform.
Collaborate and Document: you'll work closely with product engineers and business stakeholders to understand their needs. You'll also contribute to our technical direction by writing clear design documents and Architecture Decision Records (ADRs) for new patterns and tools.
Improve the Platform: you'll continuously look for, notice, and implement improvements to our data infrastructure, helping us build a well-managed and cost-effective platform.