We're seeking an innovative, solution-oriented Data Engineer to join our dynamic Data Ops team. Your mission is to develop, maintain, & scale a sophisticated platform for product & event analytics capable of handling vast amounts of data. This exciting role will see you at the heart of transformative projects, turning complex datasets into accessible insights that drive strategic decisions. As part of our team, you'll be shaping the future of data in our organization, crafting scalable data systems that can keep pace with our rapid growth. We can't wait to meet you if you're passionate about data & ready to push boundaries.

Our platform has robust analytics tools that can tell video creators where people are from, where they click, & even track where in a video someone stopped watchinggiving you insight into creating engaging content in the future.

While working as a peer to both technical & non-technical staff throughout the company, you will drive the improvement process of our products & business operations. You will help define data access & discoverability requirements & work to create infrastructure & services that provide access to event streams.

What you'll do:

• Design, develop & maintain Vimeos product & event analytics platform that processes billions of records every day in real-time to enable analytics & event-driven systems
• Partner with analytics leaders & analysts to ensure adherence to data governance & data modeling best practices
• Partner with product engineering teams to enhance the efficiency of product analytics clients & data collection mechanisms
• Contribute software designs, code, tooling, testing, & operational support to a multi-terabyte analytics platform
• Provide technical leadership to the data engineering team & actively lead design discussions
• Constantly monitor our data platform & make recommendations to enhance system architecture 
• Work collaboratively with other data engineers, analysts, & business stakeholders to understand & plan technical requirements for projects
• Prioritize project intake, perform cost/benefit analysis, & make decisions about what work to pursue that best balances our platforms users, stakeholders, & technology

Skills & knowledge you should possess:

• 7+ years of engineering experience in a fast-paced environment; 3+ years of experience in scalable data architecture, fault-tolerant ETL, & monitoring of data quality in the cloud
• Deep understanding of distributed data processing architecture & tools such as Kafka & Spark
• Working knowledge of design patterns & coding best practices
• Experience with & understanding of data modeling concepts, techniques, & best practices
• Experience with Airflow, Celery, or other Python-based task-processing systems
• Proficiency in SQL
• Proficiency in Python or Java 
• Proficiency with modern source control systems, especially Git
• Experience working with non-technical business stakeholders on technical projects

Bonus points (nice skills to have, but not needed):

• Cloud-based DevOps: AWS or Google Cloud Platform or Azure
• Experience with Amplitude, Snowplow, Segment, or other event analytics platforms 
• Relational database design
• Snowflake or other distributed columnar-store databases
• Basic Linux/Unix system administration skills
• Familiarity with containerization technologies (e.g., Docker, Kubernetes)

Targeted Base Salary Range:  $135,000 to $205,500