דרושים » ניהול ביניים » Data Analytics Team Lead

we are looking for a product-first, AI-native Data Analyst to shape how our Product organization understands signup, activation, feature adoption, and launches.
This is a high-ownership role combining strong business judgment with deep technical capabilities. You will contribute to strategic initiatives, work closely with Product Managers, engineers, and senior leadership, and help shape how decisions are made across the company.
You will work primarily with dbt, BigQuery, Looker, and GitHub, using AI-enabled tools such as Cursor, MCP integrations, n8n, and OpenClaw to accelerate and automate your work.
For us, AI-native means more than generating SQL in a chatbot. It means giving agents the right context and tools, validating their output, and turning repeatable processes into reusable workflows.
Product data is consumed throughout . Success in this role therefore requires excellent communication, proactive ownership, and the ability to translate complex analysis into practical business recommendations.
Key Responsibilities:
Partner with Product Managers and engineers to define events, funnels, activation criteria, adoption metrics, and post-launch measurement.
Analyze high-impact questions involving signup conversion, first-day behavior, feature adoption, retention, and release performance.
Contribute to strategic projects and provide leadership with trusted insights and actionable recommendations.
Define and validate analytics events, then integrate them into our usage, 360, and feature-usage models.
Extend and validate dbt models, owning changes through pull request and CI.
Build and maintain focused Looker dashboards that support product decisions.
Investigate anomalies, usage drops, tracking failures, spam, and inconsistent metrics.
Turn repeatable analyses and operational processes into agent skills, rules, and automated workflows.

We're looking for a Data Warehouse Tech Lead to drive the technical vision and execution of our data infrastructure that powers decision-making across.
You'll lead both the technology and the business coordination for our data warehouse - architecting scalable solutions while working closely with stakeholders and data providers to ensure our platform serves the entire organization's needs. This role combines deep technical leadership with strategic business partnership as we build our next-generation data stack.
We believe three things matter for every role: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll:
Lead technical architecture - design and develop scalable data warehouse solutions that support multiple products and serve the entire organization's analytics needs
Manage the technical roadmap - set strategy and guide execution for the Data Warehouse team, ensuring our platform evolves with business requirements
Drive business process coordination - translate business needs into technical requirements while establishing clear data contracts with R&D, Analytics, and external data providers
Establish and implement best practices - set technical standards for data warehouse architecture, performance tuning, and development methodologies that guide the entire team's approach to building scalable data solutions
Create and maintain sustainable data pipelines - build resilient systems capable of handling unstructured data and managing an evolving schema registry across diverse data sources
Implement advanced data modeling - create robust data structures using methodologies like dimensional modeling, and optimize ETL/ELT processes for our semantic layer
Establish data quality standards - build processes for schema evaluation, anomaly detection, and monitoring data completeness and freshness across all sources
Lead cross-team collaboration - work directly with Data Engineers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers to align technical solutions with business goals

We are looking for a highly analytical, deeply technical, and proactive Senior Salesforce and Business Applications Analyst to join our team. In this role, you will champion an AI-first approach, leveraging AI across every aspect of your work to optimize efficiency and drive innovation.

You will bridge the gap between business needs and technical execution, taking full ownership of complex systems and driving end-to-end processes. Your focus will be on supporting, enhancing, and automating our operations across various business domains, including Sales, Service, and Marketing.

This hands-on role encompasses managing daily system maintenance, configuring systems, integrating AI-driven workflows, and overseeing projects from inception to completion.

Key Responsibilities:

End-to-End Project Management: Manage complex, cross-functional projects from initial ideation, through requirements gathering, to successful deployment and optimization.
Drive Innovation & Initiative: Act as a proactive change-agent. Identify business gaps, propose innovative solutions, and passionately push new initiatives forward to improve efficiency and performance.
System Ownership: Take full accountability and end-to-end ownership of the systems health, functionality, and alignment with business goals.
Mentorship & Leadership: Guide, mentor, and upskill junior team members, fostering a culture of continuous learning and professional excellence within the team.

Required Data Analyst
Description
We're transforming the way fleets operate by leveraging data, automation, and AI to power smarter mobility. As a Data Analyst, you'll play a key role in shaping product strategy and business decisions by turning complex data into actionable insights. You'll partner with Product, Engineering, and customer-facing teams to build scalable analytics solutions, define success metrics, and uncover opportunities that drive impact across our platform
What youll do:
Own the product analytics domain for key products and strategic initiatives, with a focus on user behavior and product engagement.
Design, build, and own our product analytics infrastructure (event tracking, taxonomy, instrumentation) from the ground up, primarily using Mixpanel.
Define and maintain a clean, scalable event-tracking taxonomy in partnership with Engineering and Product.
Analyze large-scale product and behavioral datasets to identify trends, opportunities, and business insights.
Design, build, and maintain dashboards and reporting solutions using Mixpanel and other modern BI tools.
Develop automated data pipelines and analytical workflows using Python and Airflow.
Partner closely with Product Managers to define KPIs and metrics (activation, retention, funnels, engagement), measure success, and support product decision-making.
Work with customer-facing teams to provide insights and occasionally participate in customer discussions and presentations.
Build internal tools and processes that improve data accessibility and operational efficiency.
Translate complex data findings into clear recommendations for both technical and non-technical stakeholders.

The successful BI Team lead, will play a key role in managing and growing a team responsible for delivering impactful data products and solutions.
As a BI Team Lead, you will oversee the personal and professional development of your team, while also being the main point of contact for client-facing data initiatives. Youll drive data strategy and contribute to new initiatives that support cross-company objectives. This role involves collaborating with product managers, business stakeholders, and leadership to design, develop, and maintain scalable analytics solutions. You will also enhance the companys understanding of key business metrics by building automated tools and insightful visualizations in a rich data environment.
You will also be responsible for integrating AI and machine-learning capabilities into BI solutions, including developing automation processes and AI agents to support decision-making.

Required Engineering Team Lead - Data Science Team
About the Role:
A top player in its game and is heading for an exciting year.
In this role, you will take an integral part in the creation of a new and innovative SaaS product.
If you are a talented software engineer and engineering manager that likes to solve complex problems and looking for your next challenge we want you to join our team!
What youll do:
As the Team Leader of a Detection and Response Engineering team, you will lead a talented team to design, implement, and deploy scalable data solutions for an innovative SaaS product. Youll be responsible for shaping the direction of a system that impacts millions of users worldwide. If you're an experienced manager with a strong technical background, ready to lead in a dynamic, fast-paced production environment, we want you on our team!
The group responsible for 4-5 different products:
1. DRS (fully managed fraud detection solution)
2. Agentic Visibility
3. Citadel (ITP) - lean version of DRS capabilities
4. Transaction Monitoring offering
5. More might come soon
Responsibilities:
Lead and guide one of the DRS Engineering teams in the design and deployment of scalable data infrastructure.
Collaborate effectively with cross-functional teams (Data Science, Research, Security, etc.) to ensure alignment on business needs and security standards.
Manage the technical backlog, make critical decisions on product milestones, and ensure timely, secure, high-quality delivery and deployment.
Foster the growth of team members through mentorship, personal development opportunities, and the promotion of continuous improvement.
Identify, manage, and mitigate security risks across the data platform, maintaining high standards in all initiatives.
Define and implement methodologies to guarantee the performance, scalability, and quality of our data infrastructure.

As an Engineering Team Lead in R&D, you will lead a team of backend and frontend engineers building our companys product.
You will combine technical leadership, people management, and close partnership with Product and Design to deliver meaningful customer value. Your team will own the full development lifecycle, from shaping solutions and technical design through implementation, testing, deployment, and production monitoring.
Job responsibilities
Lead and develop the team - Coach and grow engineers through regular feedback, clear expectations, and meaningful ownership. Support hiring and onboarding, address performance gaps early, and build a collaborative team environment.
Shape product solutions - Partner closely with Product and Design to understand customer needs, challenge assumptions, and shape solutions. Make scope and technical trade-offs explicit to support sound prioritization.
Own delivery from end to end - Turn priorities into clear execution plans and achievable milestones. Manage dependencies, communicate progress and risks proactively, and adapt plans as new information emerges.
Provide technical leadership - Guide architecture, design, and code quality. Stay close to implementation and contribute hands-on where it creates the most value, while empowering engineers to lead.
Own production quality - Build reliability, observability, security, and performance into the development lifecycle. Ensure clear ownership of monitoring, incidents, and follow-up improvements that address root causes.
Collaborate across teams - Work with other Talent Unit teams, Architects, and platform partners to align on shared capabilities, resolve dependencies, and deliver coherent solutions.
Continuously improve how the team works - Simplify processes and solutions, encourage experimentation, and use AI-assisted development thoughtfully to improve effectiveness while maintaining engineering accountability.
Lead through change - Help the team understand priorities and their purpose, create clarity during uncertainty, and maintain trust, focus, and sustainable ways of working.

Were looking for a Analytics Engineer to own the data and analytics foundation that helps Product, Growth, Customer Success, R&D, and leadership make better decisions.
Youll own the path from raw data to actionable insight - building reliable models, defining key metrics, analyzing product and business performance, and communicating what the data actually tells us.
What youll do:
Analyze product and business performance: Track core KPIs, investigate trends and anomalies, and analyze product usage, feature adoption, customer behavior, funnels, and retention to identify opportunities for improvement.
Turn data into actionable insights: Translate analytical findings into clear recommendations that help Product, Growth, Customer Success, and leadership make better decisions.
Evaluate product initiatives: Measure the impact of new features, product changes, and experiments using appropriate analytical and statistical methods.
Own analytical data models: Develop and maintain reliable, well-structured data models that support consistent metrics, self-service analytics, and trusted business reporting.
Improve the analytics foundation: Contribute to the evolution of our analytics infrastructure, data quality, and tracking in collaboration with Engineering and other stakeholders.
Build and communicate insights: Develop dashboards and targeted analyses, and present findings clearly to technical and non-technical stakeholders, connecting results to business impact.

As an Engineering Team Lead, you will play a critical role in designing, delivering, and maintaining software that powers this transition-where reliability, precision, and performance are paramount. You will guide an agile team of full-stack engineers, balancing technical system architecture with hands-on development and people mentorship.



Responsibilities
Manage a team of 5 engineers.
Design, implement, and validate robust backoffice platform, complex business workflows, and testing infrastructure using TypeScript across React and Node.js.
Provide technical guidance, architecture mentorship, and code reviews to team members.
Collaborate with customers and internal stakeholders to transform complex banking workflows and ambiguous operational needs into clear, actionable functional specifications.
Work with the team to establish and promote high standards for code quality, developer experience, and engineering excellence.
Troubleshoot and resolve system issues, ensuring solutions are delivered effectively both independently and as part of a team.

We're looking for an experienced Data Analyst to join our growing Data team and help shape one of our core functions.

This isn't a traditional BI or Product Analytics role. You'll work across engineering, data science, product, research, and customer-facing teams to understand complex data from enterprise environments, transform it into a consistent data model, and generate insights that directly power our product and customer experience.

You'll wear multiple hats-from researching new data sources and designing scalable data models to supporting customer onboarding, surfacing meaningful insights, and helping define how our data platform evolves as the company grows. This also means getting hands-on in the codebase: you'll regularly modify logic in production system components, not just analyze data from the outside.

If you're someone who enjoys turning messy data into clear decisions, thrives in ambiguous environments, and wants to build the foundations of a data function from the ground up, we'd love to meet you.

What You'll Do

Research and evaluate new customer data sources, APIs, and integrations, understanding what data is available, how reliable it is, and how it can create value.

Analyze large, complex datasets to identify patterns, anomalies, and actionable insights that improve our product and customer outcomes.

Design and evolve our data models, creating a unified language across data coming from multiple integrations and systems.

Partner closely with Engineering and Data Science teams to define schemas, data structures, and scalable modeling approaches.

Build and modify logic in system components as part of regular delivery, not just spec it for someone else to build.

Support customer onboarding by validating incoming data, identifying issues, and ensuring customers receive meaningful insights from day one.

Deliver customer-facing analyses, reports, and recommendations while working against real customer deadlines.

Help define the foundations of our data function by evaluating tools, methodologies, and best practices that will scale with the company.

Work closely with Product to ensure product decisions are informed by data and grounded in real customer behavior.

Collaborate on AI-powered capabilities by helping define the data, signals, and requirements that enable intelligent product features and autonomous workflows.