דרושים Sr Software Engineer ב-Vimeo ב-Israel, Tel Aviv-yafo

The AI applications team is working as an end to end value stream function, delivering product solutions from the very beginning of an idea towards the final user experience, where the main expertise is around products that require AI abilities.

Responsibilities:

• Collaborate with design, front-end, and ML engineers to develop and implement new features for Vimeo's platform.
• Build scalable services and applications to support Vimeo's large-scale platform.
• Write clean, efficient, and well-documented code. Actively participate in code reviews and quality assurance processes.
• Work in a cross-functional team, closely collaborating with front-end, back-end, and AI developers to ensure seamless integration and optimal performance of front-end features.
• Identify opportunities to improve our architecture and tooling across multiple levels of the stack.
• Continuously research and explore new technologies, tools, and techniques to stay up-to-date with the latest trends and best practices.

Qualifications:

• 5+ years of technical experience working on consumer-facing products
• Experience developing services at scale with Python or Go
• Experience with Developing microservices, working with databases and APIs
• Proficiency with cloud based services and ability to work independently with cloud platforms (AWS, GCP)
• Great communication skills and a proven record of working across disciplines

Bonus Points:

• Experience with video services.
• Passion for AI applications.

Responsibilities:

• Be involved in all stages of the development life cycle, from architecture design reviews to production
• Work autonomously and be comfortable executing features from start to finish as planned
• Conduct code reviews, write unit and integration tests to improve code quality
• Proactively seek opportunities to enhance system efficiency and functionality

Qualifications:

• 4+ years of experience in backend development and API development
• Proficiency in Python programming (or similar) is essential
• Extensive familiarity with web infrastructure and databases
• Experience working with AWS/GCP is required
• Hands-on experience with the Django framework - advantage
• Proficiency in PHP - advantage

This is a senior individual contributor role with a high degree of ownership to create and drive a vision for next-level site analytics. You’ll be counted on to act independently and have a passion to innovate.

Job Responsibilities:

• Conduct strategic analysis on complex datasets, offering actionable insights for the product team and executives.
• Design, build, and maintain product-related user-friendly reports and dashboards
• Present findings and recommendations effectively to various stakeholders
• Collaborate with cross-functional teams (Product, Engineering, Design)
• Design experiments to validate hypotheses related to product and user experience optimization.
• Build user journey data models using complex datasets
• Implement a comprehensive tracking and tagging strategy, defining standards and providing guidelines for website tracking and data collection.

Skills and knowledge you should possess:

• 4+ years of experience as a data analyst, with a strong background in site-related product analytics
• Proficient in SQL with hands-on skills.
• B.Sc. in Engineering, Math, Statistics, Science/Data Systems Management, Economics or equivalent background.
• Expertise in data visualization tools (Tableau, Looker, Amplitude).
• A sense of ownership - capable of independently initiating and driving multidisciplinary projects from start to finish.
• Excellent written and verbal English communication skills.
• Deep understanding of site user journey patterns and methodologies.

Bonus Points:

• Proficiency in Python, R, or any other scripting language.
• Experience in building analytics outputs from scratch.
• Background in mobile applications analytics
• Experience in global companies

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.