לוח משרות דרושים מנהל מחלקת Data בתל אביב יפו

We are looking for a Product Data Director to lead our global product data strategy and governance. In this role, you will own the vision, implementation, and continuous improvement of how data is captured, structured, and leveraged across our product ecosystem. Youll partner closely with Product, Engineering, BI, and Operations teams to ensure data excellence, enable data-driven decision-making, and unlock insights that enhance our products, customer experience, and business growth.
Responsibilities:
Develop and execute a comprehensive product data strategy aligned with our business goals.
Define and own data standards, taxonomy, and governance frameworks across all product lines.
Partner with Product, BI, and Engineering to design scalable data models and infrastructure supporting product analytics, reporting, and performance tracking.
Lead a cross-functional data excellence initiative, ensuring high-quality, accurate, and consistent data.
Work with product managers to embed data-driven decision-making in product planning, experimentation, and optimization processes.
Oversee the implementation of data instrumentation and tracking for new product launches.
Collaborate with the Analytics and Data Engineering teams to ensure data availability and reliability across systems.

We are looking for a Data Operations Team Lead to lead and scale our data operations function. This role sits at the intersection of data, algorithms, and operations, and is critical to the success of our computer vision and AI models.
You will lead a distributed team responsible for data collection, annotation, quality control, and delivery, while working closely with Algorithm teams to understand model needs, prioritize requests, and ensure reliable, high-quality data pipelines.
This is a hands-on leadership role - you will manage people and processes, but also actively design, build, and improve data workflows.
About The Role
Lead and manage the Data Operations team, including annotation teams in Israel and a large remote team in India
Serve as the primary interface between Data Operations and Algorithm teams: understand model requirements, prioritize tasks, and plan data delivery
Own end-to-end data workflows, from model improvement needs through data definition, annotation guidelines, execution, and delivery
Ensure high data quality through close monitoring, validation, troubleshooting, and root-cause analysis
Design and maintain clear annotation guidelines, documentation, and training materials
Closely manage remote annotation teams, including weekly syncs, hands-on oversight, and deadline management
Own and operate the annotation pipeline using industry tools (e.g., CVAT)
Monitor progress, track performance, and continuously improve efficiency and quality
Own annotation budgets, monthly reporting, and validation of hours and outputs
Evaluate, benchmark, and implement new tools and processes in the data and annotation domain
Work hands-on with scripts, AI tools, and monitoring systems as needed to support data quality and operations.

we are a data driven company, the data Engineering team is the bridge between raw data and impactful business insights. You will lead a team of talented engineers to architect, build, and maintain the data infrastructure of our company. Your mission is to ensure our data is reliable, secure, and ready for everything from standard BI reporting to cutting-edge Generative AI applications. Youll act as a key partner to our business teams, translating high-level needs into technical reality and driving a massive impact on our bottom line. In addition youll spend time mentoring your team as well as tackling high-level architecture decisions, pushing technical strategy and contributing to the codebase.
What am I going to do?:

* Lead a team that designs and scales Real-Time data pipelines processing millions of events hourly.
* Utilize cutting-edge technologies to build scalable and high performant data infrastructure.
* Influence and drive architecture and data strategy decisions.
* Work closely with other stakeholders such as data Developers, Analysts, data Science and R&D.
* Hands-on development of data infrastructure tools (~50% of the time).
* Lead and mentor the team talent.
* Finops and governance of data infrastructure domains.
Equal opportunities:
At our company, we prioritize diversity. We celebrate difference and embed it into every aspect of our workplace and product, as well as our community. we are proud and committed to providing equal opportunity employment to all individuals regardless of race, color, religion, sex, sexual orientation, citizenship, national origin, disability, Veteran status, or any other characteristic protected by law. In addition, we will provide accommodation to individuals with disabilities or a special need.

We are seeking an experienced Data Team Lead to build, lead, and scale our data function. This is a hands-on leadership role that combines strategic thinking, technical excellence, and people management. You will build and manage a team of Data Engineers and Data Analysts, while working closely with senior management and cross-functional leaders to translate data into measurable business impact.
This role is ideal for someone who thrives in a fast-paced startup environment, enjoys influencing decision-making at the highest levels, and is passionate about embedding a data-driven mindset across the organization.
What You'll Do:
Lead and mentor the Data team, and support their professional growth while achieving impact goals of the marketing data structure such as: multi touch attribution model, creative analytics and automated data governance processes.
Define and own the data vision, roadmap, infrastructure, and best practices aligned with company objectives.
Act as a trusted data partner to executive leadership and senior stakeholders, influencing strategy through insights and analysis while promoting a strong data-driven culture.
Oversee the design, build, and maintenance of a scalable and reliable data warehouse.
Lead the design, implementation, and optimization of ETL/ELT pipelines to integrate data from multiple internal and external sources.
Ensure high standards for data quality, governance, integrity, and documentation.
Translate complex datasets into clear, actionable insights that support the different departments' needs and the company growth through operational excellence.
Support advanced analytics use cases including forecasting, experimentation (A/B testing), and performance measurement.
Review and elevate dashboards, reports, and analyses to ensure clarity, accuracy, and executive relevance.
Identify gaps in data collection and proactively propose solutions to improve visibility and decision-making.