Data Engineer

We are a technology company working to transform credit and banking in Latin America starting with point of sale finance. We aim to build fair, simple and affordable financial services that empower our clients, treating them with dignity, and building financial freedom. We launched in February 2019 and have already served thousands of clients and disbursed millions of dollars.

We operate as a full stack startup. We have built our core systems and processes from scratch, and we believe our technology and analytics platform will drive our progress into the years to come. We come at this with deep experience building and growing technology teams and financial products. As important as what we do is how we do it. We are a conscious company, and are deeply committed to working and living our five core values - A company of owners inspiring colleagues, we pull rabbits out of hats, we care and we trust, act with integrity, win today every day, and scale exponentially

We are backed by Andreessen Horowitz, Monashees, Village Global, and an outstanding team of individual angels, including Kevin Ryan, Josh Abramowitz, and Scott Weiss.

As a Data Engineer at ADDI, you will work closely with engineers, data analysts, data scientists and product managers to build and scale our data infrastructure architecture. Your mission will be highly focused on evolving our data infrastructure to initially serve our basic business intelligence requirements and eventually automate our most complex data use cases to train our ML models.

What you will do

• • Implement and evolve our data pipeline to improve the availability, performance and quality of the data that serves our entire organization.
  • Deploy improvements to the data pipeline on a daily basis using our CI/CD pipeline.
  • Build an initial data lineage system that will improve the traceability, compliance and governance of our data.
  • Review pull requests on a timely manner transferring your deep knowledge with your team. We expect that you provide great feedback from a technical and functional perspective.
  • Make contributions to our Architecture Decision Records repository. Your contributions will help us to improve our platform and how we work at ADDI

Requirements

• Have built data pipelines from scratch using modern data infrastructure architectures.
• Clear understanding of big data technologies and distributed systems such as Spark, Flink, Beam, Airflow, Luigi
• Great expertise working with streaming architectures on top of Apache Kafka and the Python ecosystem.
• Deep knowledge of Data Mesh, Data Lakes, Data Warehouses and Data Marts.
• Have mastered the technical requirements to get stable and scalable code into production.

Benefits

• Work on a problem that matters and help change customers’ lives.
• Build a lasting company from the very beginning, helping define every aspect of it.
• Be at the center of it all. We are a true technology company, and engineering is at the core of what we do.
• Massive market opportunity ahead of us; we are growing faster than pretty much any other fintech lender was at our stage.
• Work alongside a great and diverse team that cares about what we are doing and how we are doing it.
• Generous compensation, including equity, 100% health insurance (and 50% for dependents), flexible time-off, learning budget, and visa sponsorship for foreigners.

How the hiring process looks like

• Meet with our recruiter for a 30-minute video chat. We will get to know you better, understand what you’re looking for, and answer any questions you might have about ADDI.
• Meet with one Data Engineering Manager for a 30-minute video chat interview. Here, we will ask you questions about your technical background and basic computer science concepts. You will be able to ask any questions about the culture and how we work at ADDI.
• Complete a simple take-home challenge within a 1-week window. With this technical challenge, we want to see your technical expertise solving a real-world problem. We expect that you invest 5 hours or less in developing a working solution.
• Meet with a data software engineer and the manager for a 60-minute chat to talk about your take-home exercise submission and any questions you might have.
• Meet onsite with one of our founders for a 30-minute chat to talk about the vision of the company, what we are building and how you will contribute to our product.