Staff Data Engineer

As one of the first pioneers of earned wage access, our passion at EarnIn is building products that deliver real-time financial flexibility for those with the unique needs of living paycheck to paycheck. Our community members access their earnings as they earn them, with options to spend, save, and grow their money without mandatory fees, interest rates, or credit checks.

We’re fortunate to have an incredibly experienced leadership team, combined with world-class funding partners like A16Z, Matrix Partners, DST, Ribbit Capital, and a very healthy core business with a tremendous runway. We’re growing fast and are excited to continue bringing world-class talent onboard to help shape the next chapter of our growth journey.

• →Lead and focus on scaling the data infrastructure, streamlining the data delivery, and designing and implementing AI automation to replace manual operations.
• →Engage closely with a wide array of stakeholders, including executive, product, data, and design teams, providing high-level support for data infrastructure challenges, advising on technical data issues, and implementing self-serve solutions.
• →Develop sophisticated AI-based analytical tools that integrate with the data pipeline to provide deep insights into key business metrics, including customer growth and operational efficiency.
• →Architect and manage extensive, sophisticated data sets to meet complex business needs and requirements.
• →Engage closely with a wide array of stakeholders, including executive, product, data, and design teams, providing high-level support for data infrastructure challenges and advising on technical data issues.
• →Make a meaningful impact on the lives of our community members.
• →Collaborate and mentor other senior engineers while providing thoughtful guidance using code, design, and architecture reviews.
• →Contribute to defining technical direction, planning the roadmap, escalating issues, and synthesizing feedback to ensure team success.
• →Estimate and manage team project timelines and risks.
• →Participate in hiring and onboarding for new team members.
• →Lead cross-team engineering initiatives.
• →Constantly learning about new technologies and industry standards in data engineering.

• →7+ years in designing, building, and maintaining the Data infrastructure, and the ability to lead complex projects and teams.
• →Bachelor's, Master’s, or PhD degree in computer science, computer engineering, or a related technical discipline, or equivalent industry experience.
• →Deep knowledge of Kafka, Proficiency in programming languages like Python and Scala, and a good understanding of ML engineering. 
• →Strong knowledge of distributed computing frameworks, such as Apache Spark, with cloud platforms such as AWS, Azure, or GCP.
• →Working experience with Databricks would be nice to have
• →Experience using AI-assisted development tools (e.g., GitHub Copilot, Cursor, ChatGPT, or similar tools) as part of your software development workflow
• →Deep understanding of database design, SQL, and NoSQL databases. Experience in managing large datasets and optimizing database performance.
• →Proficiency in Git and Terraform, and experience in deploying continuous integration and continuous deployment (CI/CD) practices.
• →Experience in managing event-driven systems, particularly with Kafka in cloud environments.
• →Expertise in developing and implementing data governance frameworks, policies, and procedures to ensure data quality, compliance, and effective data management practices.
• →Deep understanding of data security principles, including encryption, decryption, and secure data storage and transfer protocol

# LI-Hybrid