Data Engineer II, Data Ops

We are looking for an innovative and solution-oriented Data Engineer to join our dynamic Data Ops team. In this role, you will be responsible for developing, maintaining, and scaling a sophisticated platform for product and event analytics. Your mission will be to turn complex datasets into accessible insights that drive strategic decisions, and to shape the future of data in our organization. If you are passionate about data and ready to push boundaries, we can't wait to meet you.

• Design, develop and maintain Vimeo's product and event analytics platform
• Process billions of records every day in real-time to enable analytics and event-driven systems
• Ensure adherence to data governance and data modeling best practices
• Enhance the efficiency of product analytics clients and collection mechanisms
• Contribute software designs, code, tooling, testing, and operational support to a multi-terabyte analytics platform
• Provide technical leadership to the data engineering team and actively lead design discussions
• Monitor data platform and make recommendations to enhance system architecture
• Work closely with other data engineers, analysts, and business stakeholders to understand and plan technical requirements for projects

• 3+ years of engineering experience in a fast-paced environment
• 2+ years of experience in scalable data architecture, fault-tolerant ETL, and monitoring of data quality in the cloud
• Deep understanding of distributed data processing architecture and tools such as Kafka and Spark
• Working knowledge of design patterns and coding best practices
• Experience with and understanding of data modeling concepts, techniques, and best practices
• Experience with Airflow, Celery, or other

• Opportunity to work on transformative projects and shape the future of data
• Access to robust analytics tools for creating engaging content
• Collaboration with both technical and non-technical staff
• Opportunity to drive improvement process of products and business operations
• Ability to define data access and discoverability requirements
• Technical leadership and active participation in design discussions
• Constant monitoring of data platform and recommendations for system architecture enhancement
• Collaboration with data engineers, analysts, and business stakeholders
• Opportunity to work with cloud-based DevOps (AWS or Google Cloud Platform)
• Experience with event analytics platforms (Amplitude, Snowplow, Segment)
• Knowledge of relational database design
• Familiarity with Snowflake or other distributed columnar-store databases
• Basic Linux/Unix system administration skills
• Equal opportunity employer with a focus on diversity, equity, and inclusion