ABOUT US

ODDITY is a consumer-tech company which builds and scales digital-first brands to disrupt offline-dominated categories.

With HQ in New York City and an R&D center in Tel Aviv, we built one of the industry’s most advanced technology platforms, which leverages data science, machine learning and computer vision capabilities to deliver an unparalleled online experience for consumers. We are using cutting-edge data science to identify consumer needs and develop solutions in the form of tech and wellness products.

In less than 5 years since launch, we have built two of the fastest-growing online beauty brands in the US-IL MAKIAGE and SpoiledChild. Our first brand IL MAKIAGE has since grown to unprecedented scale online, reaching over $300 million in revenue and 40 million users in only 4 years. ODDITY New Ventures built and launched our second brand SpoiledChild in early 2022, and it is already scaling even faster than IL MAKIAGE. As of 2023, ODDITY is officially a publicly traded company valued at >$2B and we were named a TIME100 Most Influential Company.

Our continued success is a result of our winning mindset combined with unparalleled physical & tech products. We have made significant investments in data science, AI, computer vision, and biotechnology to identify consumer needs and develop solutions designed for consumers. Our proprietary computer vision technology allows smartphone cameras to capture hyperspectral wavelengths of light beyond the capability of the human eye. In 2023, ODDITY acquired Revela - a biotech start-up that uses AI-based molecule discovery to bring next-generation, proprietary ingredients to the beauty & wellness market.

About the Role

We are looking for a hands-on Data Engineering Team Lead to guide the design, development, and scaling of our data platform and pipelines. You will lead a small team of data engineers while remaining actively involved in implementation, architecture decisions, and cross-functional collaboration.

This role is ideal for someone who is still deeply technical but also ready to take ownership of delivery, planning, and team coordination.

Key Responsibilities

· Lead a data engineering team delivering reliable, scalable data pipelines and data models

· Design, build, and maintain ETL and ELT pipelines

· Own data workflows and scheduling using AWS MWAA (Managed Airflow), including orchestration and migration jobs

· Develop and optimize data processing pipelines using AWS Glue

· Build robust data transformations using Python and SQL

· Work with large-scale distributed processing using PySpark (strong advantage)

· Manage and optimize data warehouse structures in Amazon Redshift (or equivelent)

· Ensure data quality, consistency, and performance across pipelines and datasets

· Collaborate closely with Product, Marketing, and Data Analytics teams to translate business requirements into data solutions

· Support BI use cases and verify data availability for reporting in Looker

· Manage work tracking, sprint planning, and delivery using Jira

· Participate in architecture discussions and drive best practices across the data

· Be in charge and available and make sure our system is 24/7 online.

Required Skills & Experience

· 3+ years of experience in data engineering

· Strong SQL skills (critical requirement)

· Strong programming skills in Python

· Experience building ETL / ELT pipelines

· Experience with AWS data services, especially:

·AWS Glue

·AWS MWAA (Airflow)

·Amazon Redshift

· Experience working with data warehouses and large datasets

· Familiarity with BI tools, preferably Looker

· Experience working in agile environments using Jira

Nice to Have (Big Advantage)

· Eexperience with PySpark

· Experience working directly with marketing / product analytics teams

· Understanding of data modeling for analytics and BI layers

· Experience leading small engineering teams or mentoring engineers

· Exposure to cloud data architecture best practices (scalability, cost optimization, governance)

Collaboration & Leadership Expectations

· Act as a bridge for engineering and business teams

· Work closely with Product and Marketing teams to define data requiremnts and deliver actionable insights

· Help shape roadmap priorities alongside technical and business leadership

· Promote engineering best practices, code quality, and maintainable pipelines

· Always improve and help attitude is mandatory