Data Engineering Tech Lead
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, fastly-growing startup, we’re on the cusp of our next growth spurt. It’s the perfect time to join our team of ~300 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.
We are looking for an experienced Data Engineering Tech Lead with a strong technical background in data infrastructure, data architecture design and robust data pipes building. The candidate must have the ability to lead the design and development of key features and interact effectively with cross-functional teams. You should have a passion for exploring new technologies and solving complex data challenges. You will be a center of knowledge, consult and share your expertise and enforce best practices.
- Play a significant role in developing 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.
- End-to-end development of data crunching and manipulation processes within 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 ML features and models into Optimove product.
- B.Sc. in Computer Science, Industrial Engineering and Management, Information Systems, or similar major
- 5+ 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 microservices 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
- Experience with Snowflake and MSSQL
- Experience with MLOps and ML implementations
- Experience with Docker and Kubernetes
- Experience with GCP services
- Experience with PubSub/Kafka