Data Infrastructure Engineer Intern

Job not on LinkedIn

🔥 0 minutes ago

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Sezzle

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2016

💳 Fintech

🛍️ eCommerce

👥 B2C

💰 $225M Post-IPO Debt - Sezzle on 2024-05

Fintech • eCommerce • B2C

Sezzle is a fintech company that provides buy-now-pay-later (BNPL) payment solutions. It enables consumers to split online purchases into interest-free installment payments and offers merchants a checkout option and integrations to increase conversion and average order value. Sezzle operates primarily in North America and serves both consumers and e-commerce merchants.

📋 Description

• Assist in maintaining and improving data warehousing systems using AWS DMS and Redshift • Monitor data pipelines, identify issues, and troubleshoot basic problems • Write and optimize SQL queries for analytics and data validation • Collaborate with engineers and analysts to understand data needs and support use cases • Participate in testing, documentation, and reliability improvements for data systems • Identify and automate repetitive daily manual processes to reduce operational overhead and improve team efficiency • Learn and explore new tools and technologies in the data ecosystem

🎯 Requirements

• Currently pursuing or recently completed a degree in Computer Science, Data Engineering, or a related technical field • Basic understanding of relational databases, including MySQL, Postgres, and relational concepts • Basic understanding of NoSQL databases • Familiarity with at least one programming language, such as Python or Go • Interest in data infrastructure, distributed systems, or backend engineering • Demonstrated experience working with Claude or equivalent large language model tools is required • Comfortable leveraging AI to enhance productivity, research, and communication • Exposure to cloud platforms, preferably AWS • Basic understanding of data pipelines or ETL concepts • Awareness of data warehousing concepts • Interest in big data or streaming technologies such as Kafka, Kinesis Streams, or Flink • Strong problem-solving skills and willingness to learn • Ability to work in a collaborative team environment

🏖️ Benefits

• Career advancement opportunities • Exposure to new tools and technologies in the data ecosystem • Collaborative team environment • Learning and development through real-world data engineering work • AI tools to enhance productivity and research