Vimeo Sr Director Data Engineering 

Israel, Tel Aviv District, Tel Aviv-Yafo 

38847659

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.