Data Engineer

Who we are:

Resident is an industry leader in the Direct-to-Consumer (e-commerce) space. While our customers are primarily based in the US, our R&D, Product, and Data teams have been operating out of Tel Aviv since our founding. Our mission is simple: we are building a best-in-class e-commerce platform that leverages data and technology to create a competitive advantage for our brands. Starting from the marketing acquisition funnel and continuing through each customer’s journey, our tools and technology enable us to go the extra step to deliver a world-class customer experience.

Our company is built around continuously improving our ability to introduce new customers to our products and wow them with exceptional experiences through the shopping and post-purchase journey.  We love to use data and metrics to drive our decisions while keeping in mind that customers don’t speak in numbers and that each one should be treated as a member of our family.  Oh, and by the way, you’ll get to work with a diverse group of experts around the globe. You can expect a hard-working team of people who understand how to create meaningful connections and get great work done virtually - it’s in our nature!

What we do:

We shape the business decision-making process by providing the business units with the data as well as insights about the risks and potential of their initiatives. We make sure to capture the opportunities that require strong data foundations, and we invest heavily in unlocking opportunities that require advanced data modeling. 

What You’ll Be Doing:

We are looking for a brilliant, quick-learner Data Engineer for our data engineering team - an independent, logical thinker who understands the importance of data structuring for macro-business decisions. The position combines high technical skills with a business orientation. It involves working closely with the analysts, product, and the R&D team and directly affecting the company's cross-department decisions. Our Data Engineer should be able to design and build a data flow from the API or source requirements with the most suitable tools to fit the data product requirements. They need to speak in technical and practical terms and, more importantly, lead from one to the other while dealing with challenges, independent learning, and creating them to make our team even better. 

Roles and Responsibilities:

• Designing and building full data pipelines: From defining source structures to delivering clean, organized data ready for analysis, your work ensures analysts have everything they need to make smart, data-driven decisions
• Translating business needs into scalable data solutions involves staying close to the roadmap, understanding technical nuances, and delivering purpose-built pipelines and tools
• Writing high-quality, maintainable code: Following best practices while leveraging modern data engineering tooling and CI/CD principles
• Solving complex data challenges creatively: Whether it's device identity (Device Graph), online-to-offline matching, privacy compliance, or server-to-server integrations
• ֿManaging multi-source data environments: We bring in data from over 50 sources (Marketing, Product, CS, CRM, Ops, and more), and you will assist in tying it all together into a reliable, insight-ready system
• Keeping quality and reliability top of mind: Monitor, validate, and improve data quality while ensuring robust processes across the stack

Requirements:

• B.A / B.Sc. degree in a highly quantitative field 
• 4+ years of hands-on experience in data engineering, building data pipelines, writing complex SQL, and structuring data at scale
• Fast learner with high attention to detail, and proven ability and passion to multitask on several projects at a time
• Strong communication skills and a proven ability to collaborate effectively with different stakeholders on various projects and business/technical goals
• Google Cloud Data tools (BigQuery, Cloud Composer/Airflow, Pub/Sub, Cloud Functions) or parallel tools on AWS
• Fluent in Python, including experience working with APIs, building infrastructure tools (like custom Airflow operators), and managing data streams
• High business intuition and analytical mindset, with a strong sense of how to turn raw data into insights and impact
• Experience in designing and building scalable data systems for various data applications - an advantage
• Experience in designing scalable data systems and analyzing data for insights - an advantage
• Background in data-driven companies in large-scale environments - an advantage