Vimeo is seeking a Director of Data Engineering to lead their data strategy, architecture, and automation efforts, aiming to develop a modern, scalable lakehouse architecture with Databricks on Google Cloud Platform. The goal is to ensure Vimeo's data infrastructure is scalable, cost-effective, and future-proof, while overseeing production automation and reliability for data workflows.
Requirements
- Deep expertise in modern cloud data platforms, ideally Google Cloud
- Strong background in full-stack data engineering, including orchestration (Airflow, dbt), streaming (Kafka, Flink), and distributed computing.
- Experience in automating data workflows, optimizing query performance, and implementing observability frameworks.
- Hands-on experience with data catalogs, metadata management, and governance frameworks.
- Experience with Databricks Unity Catalog and Atlan for access control frameworks.
- Experience with CI/CD, dbt, Airflow, and Terraform for automation.
- Experience with Apache Spark, SQL engines, and cloud-native services for data processing.
Responsibilities
- Design and implement Vimeo’s lakehouse architecture, leading an enterprise migration from Snowflake to Databricks
- Build and scale data processing pipelines (batch and real-time) using Apache Spark, SQL engines, Airflow, and cloud-native services.
- Drive data modeling and optimization strategies to ensure high-performance analytics, machine learning, and product insights.
- Ensure seamless integration between storage, compute, and analytics layers, supporting both structured and unstructured data.
- Lead automation-first initiatives for data ingestion, transformation, and governance using CI/CD, dbt, Airflow, and Terraform.
- Establish observability, monitoring, and fault-tolerance frameworks to ensure high uptime and performance across data workflows.
- Optimize cost efficiency and scalability of compute-intensive workloads by leveraging auto-scaling, caching, and federated query optimizations.
Other
- 8+ years of experience in data engineering, analytics, or data architecture, with 3+ years in a leadership role.
- Ability to set and execute a long-term vision for data infrastructure, automation, and reliability.
- Experience building and scaling high-performing teams across data engineering, analytics, and governance.
- Strong cross-functional collaboration skills, with the ability to influence technical and business stakeholders.
- Communicate findings and insights effectively to both technical and non-technical stakeholders.
