Sr. Director, Data Engineering

Vimeo is seeking a visionary Senior Director of Data Engineering to lead our data platform team in building scalable, high-performance infrastructure on the Databricks stack. This role requires a hands-on leader with expertise in full-stack development, automation-first engineering, and cloud-native data platforms. You will manage a team of Senior Engineers and Data Engineering Managers, driving technical excellence and fostering a culture of innovation.

 What you'll do:

• Lead, mentor, and inspire a team of Data Engineers working in cross-functional squads alongside analysts in building robust, high-performance data platforms leveraging modern technologies like Python, Spark/PySpark, and cloud-native services, emphasizing scalability, automation, and resilience.
• Drive the development of real-time streaming data platforms and batch processing systems using modern tools such as Spark Streaming, Apache Airflow, and data transformation frameworks.
• Architect data models within a medallion architecture to create reusable, maintainable, and stable data infrastructure that are easily consumed by Business Intelligence applications (Looker)
• Lead the seamless integration of data platform services with application development, contributing to full-stack solutions that effectively bridge data infrastructure and business intelligence applications.
• Establish and maintain comprehensive monitoring, logging, and alerting systems for data platform services, utilizing DevOps tools to ensure high availability and scalability.
• Partner with cross-functional teams to translate complex business requirements into robust technical platform solutions, prioritizing automation-friendly approaches for new builds
• Lead migration efforts of legacy infrastructure to target-state modern data stacks
• Optimize resource allocation, ensuring the acquisition and deployment of top-tier talent and essential tools to meet project and operational needs
• Set clear performance expectations, conduct regular reviews, and provide constructive feedback to foster a culture of high performance.
• Proactively identify and mitigate potential risks to the data platform's reliability and performance, developing robust contingency plans.
• Own the strategic architecture and hands-on implementation of comprehensive data platform solutions, from data ingestion and processing to platform service deployment, with a strong focus on automation and CI/CD best practices.

Skills and knowledge you should possess:

• BS/MS in Computer Science, Software Engineering, or a related discipline.
• 12+ years of experience in building and operating production-grade data platforms, with a strong emphasis on full-stack development and automation.
• 5+ years of experience in managing and leading data engineering teams.
• Deep understanding of software engineering best practices, including version control (Git), CI/CD pipelines, testing frameworks, and code reviews.
• Extensive expertise in cloud-native data architectures (AWS, GCP, or Azure), Spark/PySpark, Python, and modern data platform technologies.
• Understanding of Business Intelligence applications (Looker) and best practices for building sustainable underpinning data infrastructure
• Ability to automate data quality monitoring, data governance, and master data management processes.
• Proven track record of delivering impactful data platform products, including data APIs, automated reporting tools, and self-service data platforms.
• Familiarity with event-driven architectures and streaming data platforms (Kafka, Kinesis, or similar technologies).
• Expertise in Python, Spark/PySpark, and cloud-based data processing for large-scale data manipulation and automation.
• Proficiency in data platform automation using Apache Airflow, data transformation tools, and workflow orchestration systems.
• Experience in building and integrating RESTful APIs and event-driven services.
• Solid understanding of software development methodologies, including Agile, DevOps, and DataOps.

Nice-to-haves/Bonus Points:

• Experience with SQL databases, data visualization tools, and large-scale data analytics platforms.
• Hands-on experience (professional certification preferred) with cloud-based data platforms (AWS, Google Cloud Platform, Azure).
• Basic Linux/Unix system administration skills and shell scripting.
• Familiarity with machine learning pipelines, including MLOps practices and model deployment.
• Experience with real-time analytics tools and data streaming technologies.
• Strong understanding of DevOps practices, including CI/CD, infrastructure as code (Terraform, Pulumi), and monitoring tools (Prometheus, Grafana).
• Proficiency in containerization and orchestration technologies, such as Docker and Kubernetes, for building scalable data platform services.
• Experience in developing and deploying microservices and serverless applications.

About us:

Vimeo is the world’s leading all-in-one video software solution. Our platform enables any professional, team, and organization to unlock the power of video to create, collaborate and communicate. We proudly serve our growing community of over 200 million users — from creatives to entrepreneurs to the world’s largest companies.

Vimeo is headquartered in New York City with offices around the world. At Vimeo, we believe our impact is greatest when our workforce of passionate, dedicated people, represents our diverse and global community. We’re proud to be an equal opportunity employer where diversity, equity, and inclusion are championed in how we build our products, develop our leaders, and strengthen our culture.

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