Data Engineer

About Treasury Prime

Our mission is to empower developers to build new and amazing financial products by making it easy to connect with banks. Our APIs provide a wide range of banking services, from opening and servicing accounts to making payments, issuing cards, and more. We're experts at managing banks' legacy systems, and our deep integrations give our APIs the power to do anything the bank can do. We're helping banks and fintech developers build great products. Treasury Prime is the best way for banks to modernize their software stack and for fintech developers to find the best bank partner and get to market fast. 

We run on AWS cloud services and operate cloud-based data processing environments. We're looking for a data engineer to join our data team and design, build, and maintain our data pipelines and ETL processes, enabling data flow across our platforms. Collaborating with cross-functional teams, you will ensure that data is secure, accurate, accessible, and optimized for analytics, supporting our mission to deliver actionable insights to clients.

This is an excellent opportunity to join a small team of talented engineers, take ownership of key product areas, and join the team enabling the next generation of fintech innovation!

You will:

• Build and Optimize Data Pipelines: Design, develop, and maintain scalable ETL processes and data pipelines to ingest, transform, and integrate diverse data sources utilizing tools such as Dagster, Airbyte, Kestra and Prefect with special emphasis in process automation.
• Data Modeling and Transformation: Utilize data manipulation tools like dbt to create and manage data models that drive analytics and reporting.
• Collaborate Across Teams: Partner with product managers, data analysts, and software engineers to understand data requirements and deliver tailored solutions.
• Ensure Data Quality: Implement data validation, testing, and monitoring processes and systems to ensure the integrity, reliability and confidentiality in all datasets.
• Support Analytics: Work closely with the analytics engineering team to create datasets optimized for BI tools such as Looker, Sigma and to provide actionable insights.
• Ensure Scalability and Performance: Continuously optimize workflows for performance, scalability, and cost-efficiency.

You may be a good fit for this role if you:

• 3+ years of experience as a Data Engineer, Analytics Engineer, or in a similar role within a SaaS or fintech environment.
• Strong proficiency in SQL, experience with dbt for data modeling and transformation, and EL tools such as Airbyte.
• Hands-on experience building ETL processes and data pipelines using tools such as Apache Airflow, Prefect, or similar.
• Previous experience working with cloud-based data platforms like Snowflake, BigQuery, or Redshift.
• Experience designing, building, and maintaining data pipelines, and hands-on coding experience using Python or Java is a big bonus. 
• Solid understanding of data warehousing concepts and best practices.
• Strong analytical skills and a proactive approach to identifying and addressing challenges in data workflows. 

• Think systematically and are effective in navigating ambiguously defined problem spaces.
• Be able to communicate complex ideas simply and effectively.
• Thrive in a team-oriented, fast-paced start-up environment and excited to create new things.

While these are not hard requirements for the job, the best candidates will meet many of these criteria.

We look forward to hearing from you!