About the role
About EarnIn 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. POSITION SUMMARY We are looking for an experienced Staff Data Engineer proficient in Data infrastructure operations, automation, and management, as well as traditional data engineering
responsibilities. As a Staff Data Engineer, you will work cross-functionally with various teams and contribute to helping build an enterprise-grade Data Platform. This position will be hybrid from our Bengaluru office, as part of our expanding site, with 2+ days in the office. EarnIn provides excellent employee
benefits, including healthcare, internet/cell phone reimbursement, a learning and development stipend, and opportunities to collaborate with and travel to our Mountain View HQ and Bangkok Site. Our salary ranges are determined by role, level, and location.
WHAT YOU'LL DO 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
