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.

As a Data Engineer, you’ll report to the Data Science Manager and work closely with both our Data Science and Product teams. This role requires prior, proven experience building highly scalable ETL pipelines using Databricks and AWS—we’re looking for someone who has successfully designed, implemented, and maintained large-scale data infrastructure in a production environment.

This role is ideally based in Israel, but strong candidates from the U.S. will also be considered.

Our Mission:

Nift’s mission is to reshape how people discover and try new brands by introducing them to new products and services through thoughtful "thank-you" gifts. Our customer-first approach ensures businesses acquire new customers efficiently while making customers feel valued and rewarded.

We are a data-driven, cash-flow-positive company that has experienced 731% growth over the last three years. Now, we’re scaling to become one of the largest sources for new customer acquisition worldwide. Backed by investors who supported Fitbit, Warby Parker, and Twitter, we are poised for exponential growth and ready to demonstrate impact on a global scale. Read more about our growth here.

What you will do:

• Architecture & storage: Design and implement our data storage strategy (warehouse, lake, transactional stores) with scalability, reliability, security, and cost in mind
• Pipelines & ETL: Build and maintain robust data pipelines (batch/stream), including orchestration, testing, documentation, and SLAs
• Reliability & cost control: Optimize compute/storage (e.g., spot, autoscaling, lifecycle policies) and reduce pipeline fragility
• Engineering excellence: Refactor research code into reusable components, enforce repo structure, testing, logging, and reproducibility
• Cross-functional collaboration: Work with DS/Analytics/Engineers to turn prototypes into production systems, provide mentorship and technical guidance
• Roadmap & standards: Drive the technical vision for data platform capabilities and establish architectural patterns that become team standards

What you need:

• Experience: 5+ years in data engineering, including ownership of data infrastructure for large-scale systems
• Software engineering strength: Strong coding, debugging, performance analysis, testing, and CI/CD discipline; reproducible builds
• Cloud & containers: Production experience on AWS, Docker + Kubernetes (EKS/ECS or equivalent)
• IaC: Terraform or CloudFormation for managed, reviewable environments
• Data engineering: Expert SQL, data modeling, schema design, modern orchestration (Airflow/Step Functions) and ETL tools
• Warehouses & Data Lakes: Databricks (experience is a must), Spark, Redshift and Data lake formats (Parquet)
• Monitoring/observability: Data monitoring (quality, drift, performance) and pipeline alerting
• Collaboration: Excellent communication, comfortable working with data scientists, analysts, and engineers in a fast-paced startup
• PySpark/Glue/Dask/Kafka: Experience with large-scale batch/stream processing
• Analytics platforms: Experience integrating 3rd party data
• Experience building data products on medallion architectures
• Be mission-oriented: Proactive and self-driven with a strong sense of initiative; takes ownership, goes beyond expectations, and does what's needed to get the job done

What you get:

• Competitive compensation, flexible remote work
• Unlimited Responsible PTO
• Great opportunity to join a growing, cash-flow-positive company while having a direct impact on Nift's revenue, growth, scale, and future success