Data Engineer - Remote

Posted Yesterday

Data Analysis

Full Time

USA, Israel

Overview

Nift is disrupting performance marketing, delivering millions of new customers to brands every month. We’re actively looking for a hands-on Data Engineer to build and scale the data and ML platform that powers product decisions and production models.

In Short

Design and implement data storage strategies with scalability and reliability in mind.
Build and maintain robust data pipelines, including orchestration and testing.
Optimize compute/storage costs and reduce pipeline fragility.
Refactor research code into reusable components and enforce testing and logging standards.
Collaborate with Data Science and Engineering teams to turn prototypes into production systems.
Drive the technical vision for data platform capabilities.

Requirements

5+ years in data engineering with ownership of large-scale systems.
Strong coding and debugging skills, with CI/CD discipline.
Production experience on AWS, Docker, and Kubernetes.
Expert in SQL, data modeling, and ETL tools.
Experience with Databricks, Spark, and data lake formats.
Excellent communication skills and ability to work in a fast-paced startup environment.

Benefits

Competitive compensation and flexible remote work.
Unlimited Responsible PTO.
Opportunity to directly impact company growth and success.

Nift

Nift is a pioneering company in the performance marketing space, dedicated to transforming how consumers discover and engage with new brands. By offering thoughtful 'thank-you' gifts, Nift helps businesses efficiently acquire new customers while ensuring that customers feel valued. With a strong focus on data-driven strategies, Nift has achieved remarkable growth, boasting 100% year-over-year increases for three consecutive years. The company is backed by notable investors and is on a trajectory to become a leading source for customer acquisition globally. As a well-managed and cash-flow-positive startup, Nift is poised for exponential growth and is committed to reshaping the marketing landscape.

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