Senior Data Engineer

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4 days ago

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Sezzle

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Fintech • B2C • eCommerce

Sezzle is a financial technology company that offers a "buy now, pay later" service, allowing consumers to purchase products and pay for them in four interest-free installments over six weeks. The Sezzle app provides users with a flexible financing alternative to traditional credit cards, enabling instant approval decisions without impacting credit scores. Sezzle partners with various top brands, including Amazon, Walmart, and Target, to offer in-app and in-store payment options. The company's mission is to empower consumers financially by providing more financial freedom and control. It is available as a mobile app, with millions of downloads and high user ratings, and works towards accessibility and inclusion on its platform.

201 - 500 employees

Founded 2016

💳 Fintech

👥 B2C

🛍️ eCommerce

📋 Description

• Design, build, and optimize large-scale, high-performance data pipelines to support analytics, product insights, and operational workflows. • Architect and evolve Sezzle’s data ecosystem, driving improvements in reliability, scalability, and efficiency. • Lead development of ETL/ELT workflows using Redshift, DBT, AWS DMS, and related modern data tooling. • Partner with cross-functional teams (engineering, analytics, product, finance, risk) to gather or adapt requirements and deliver robust, high-quality datasets. • Evaluate and integrate new technologies, guiding the evolution of Sezzle’s data stack and infrastructure. • Optimize Redshift and warehouse performance, including query tuning, modeling improvements, and cost management.

🎯 Requirements

• 9+ years of experience in data engineering, with a strong track record of production-grade systems. • Deep expertise with AWS Redshift or similar products, including performance tuning, table design, and workload management. • Strong hands-on experience with ETL/ELT frameworks, especially DBT, AWS DMS, and similar tools. • Proficiency in SQL (advanced level) and at least one programming language such as Python, Scala, or Java. • Experience building and maintaining AWS-based data platforms, including S3, Lambda, Glue, or EMR. • Track record designing scalable, fault-tolerant data pipelines using modern orchestration tools (Airflow, Dagster, Prefect, etc.) processing more than 100GB - 1 TB of new data a day. • Strong understanding of data modeling, distributed systems, and warehouse/lake design patterns. • Ability to work in a fast-paced, collaborative environment with excellent communication and documentation skills.