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Optimove is a global marketing tech company, recognized as a Leader by Forrester and a Challenger by Gartner. We work with some of the world's most exciting brands, such as Papa John's, Staples, and Entain, who love our thought-provoking combination of art and science. With a strong product, a proven business, and the DNA of a vibrant, fast-growing startup, we're on the cusp of our next growth spurt. It's the perfect time to join our team of ~400 thinkers and doers across NYC, LDN, TLV, and other locations, where 2 of every 3 managers were promoted from within. Growing your career with Optimove is basically guaranteed.

Our Data Engineering team is part of the RnD organization and it plays a significant role in almost every major feature we are releasing to production.

The ideal candidate is an experienced Data Engineer with a strong technical background in data infrastructure, data architecture design, and robust data pipe building.

The candidate must have the ability to lead the design and development of key features and interact effectively with other teams, Product managers, DevOps engineers, Data scientists, onboarding engineers, and Support staff.

Responsibilities:

Play a significant role in deploying and maintaining critical data pipelines in production.
Lead strategic technological initiatives and long-term plans from initial exploration and POC to going live in a hectic production environment.
Design infrastructural data services and coordinate with the Architecture team, R&D teams, Data Scientists and Product Managers to build scalable data solutions.
Work in Agile process with Product Managers, and other TLs.
End-to-end responsibility and development of data crunching and manipulation processes within the Optimove product.
Design and implementation of data pipelines and data marts.
Create data tools for various teams (e.g. onboarding teams) that assist them in building, testing, and optimizing the delivery of the Optimove product.
Explore and implement new data technologies to support Optimove’s data infrastructure.
Work closely with the core data science team to implement and maintain ML features and tools.

Requirements

B.Sc. in Computer Science, or equivalent
3+ years of extensive experience with programming languages (preferably, Python) – a must!
3+ years of extensive SQL experience (preferably working in a production environment) – a must!
Strong capability of schema design and data modeling
Experience in building robust and scalable data pipelines in a micro-services environment
Experience with data services orchestration tools, such as Airflow
Quick, self-learning and good problem-solving capabilities
Good communication skills and collaborative
Process and detailed oriented
Passion to solve complex data problems

Desired: