דרושים » הנדסה » Analytics Engineer (Artifactory Product Analytics)

Were looking for a Data Analyst to join our growing data team and help make analytics a core part of how we build. Youll work on the product-usage side of an AI product that thousands of developers rely on - understanding how teams adopt AI code review, which features drive value, and where we can make the experience better. Its a product-focused role at heart, reaching into business, operational, and cost metrics too, with room to shape how we work as the team grows.

Be the go-to analyst for the product team - drive product analytics day to day: how developers use our AI features, plus retention and conversion funnels.
Turn raw product and usage data into clear, consistent metrics the team can trust.
Build and maintain the modeled data layer, so metrics live in one place and analysis is repeatable rather than rebuilt each time.
Build and maintain dashboards so teams can self-serve answers.
Run deep-dive analysis to surface opportunities and support product decisions and experimentation.
Extend into business and operational KPIs - conversion, churn, segmentation, customer value - and cost / unit-economics.
Take analyses from problem definition through to clear recommendations, not just reports.

We are looking for a Senior Data Engineer to build and scale the data foundation behind platform and products. You will own complex data end-to-end - from ingestion and transformation through modeling, quality, observability, and production delivery.
This is a hands-on senior IC role for a strong builder who can solve difficult data problems independently, set a high technical bar, and collaborate closely with engineering, DS, and product. You will turn large, fragmented datasets into reliable, reusable capabilities that power every product.
Responsibilities
Build and own scalable data pipelines- Design, implement, and operate robust pipelines for high-volume structured and unstructured data, with validation, monitoring, lineage, and recovery built in.
Scale the platform for growth- A key near-term initiative is re-architecting the system to support a significantly larger customer base. You will own performance and cost-efficiency across pipelines and services, keeping reliability and operating costs under control as the platform scales.
Build across the stack- This is not a pipelines-only role. You will also write backend services and some frontend, including the internal backoffice the team runs on. We hire builders, not narrow specialists.
Own the core data tables- Own schema design and evolution, data contracts, and the modeling standards the team follows - naming, shared dimensions, normalization, documentation. Be accountable when a table is wrong, late, or drifting.
Level up the teams data work- Pair with and advise software engineers and data scientists on Spark, SQL, and modeling, and help turn notebook-grade code into production-grade pipelines.
Partner cross-functionally- Translate product, client, compliance, and business requirements into clear technical designs and dependable production systems.

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

Were looking for a Data & Analytics Team Lead to manage and grow our data team and own the data layer behind our AI. Youll lead a team of data analysts responsible for neural-network model analysis, model performance tracking, customer-facing and internal BI. Youll act as both the people manager and the technical lead for the team, setting technical direction while staying hands-on.
Youll thrive in this role if youre passionate about turning data into better AI products, enjoy solving complex analytical problems, and like working at the intersection of Data, Analytics, and Artificial Intelligence.
Responsibilities:
Lead the data strategy supporting AI model development, evaluation, and continuous improvement
Define KPIs and monitoring frameworks for AI model performance.
Analyze NN model outputs, build and maintain model-tracking and performance-evaluation workflows
Drive close calibration with the Algo, Product, and Data Engineering teams to align data definitions, pipelines, and metrics
Stay hands-on with SQL, Python, BI tooling, and the modern data stack
Build and own agentic data workflows - designing the context, tooling, and data access that let AI agents reliably query, analyze, and act on company data

We are looking for an experienced Analytics Engineer to join our Clinical Value team and develop the data foundations, infrastructure, and analytical tools that enable our work.
This hybrid role combines Analytics Engineering with hands-on data analysis. You will translate complex analytical and clinical needs into scalable, reliable, and reusable data solutions.
You will design data models, pipelines, analytical layers, and tools that enable complex Clinical Value studies across products and customers, while remaining hands-on with selected analytical projects.
You are expected to be independent, proactive, and impact-oriented, taking end-to-end ownership of technical challenges and opportunities for improvement.
evaluation.
Responsibilities:
Design, build, and maintain the data infrastructure supporting Clinical Value analyses, including reusable data models, pipelines, analytical layers, and tools.
Own the technical and analytical implementation of complex Clinical Value applications, adapting established methodologies to different products, customers, and real-world data environments.
Develop complex analytical solutions into reusable and scalable frameworks, enabling broader and more efficient execution across the team.
Identify data-quality issues, technical bottlenecks, and repetitive processes, and develop solutions and automation to improve reliability and efficiency.
Work closely with analysts, Data Engineering, and other technical teams to translate analytical needs into effective, maintainable data solutions and establish best practices.
Lead selected hands-on data-analysis projects, analyzing complex clinical and operational datasets to generate credible, actionable conclusions.
Collaborate with Go-to-Market teams, including Customer Success, to understand customer needs and support impactful customer-facing value demonstrations.

We are looking for a highly analytical AI Product Analyst to join our core Product Analytics tech team. Operating at the intersection of data, Product and Tech, you will be the bridge between user behavior and model performance. You will partner with Product and Tech leadership to define KPIs, build the semantic layer for Product Agents, and iterate on AI outputs. Your insights will directly impact our strategy, drive feature adoption, shape our data infrastructure, and deliver measurable business impact.
Job responsibilities
Empower Strategic Decisions: Translate complex usage data into executive-ready dashboards and actionable recommendations that align cross-functional stakeholders.
Enable AI Data Infrastructure: Build and maintain the semantic layer for Product Agents to unlock intelligent, self-serve data discovery across the organization.
Drive Product Growth: Analyze the user journey to proactively identify adoption gaps and friction points, accelerating feature activation, retention, and growth.
Optimize AI & Feature Impact: Measure roadmap launches and iterate on prompt engineering and model evaluation to continuously elevate AI performance and user experience.
Standardize Metrics & Tracking: Partner with Product leadership to define core KPIs, unify metric definitions, and establish robust event tracking.
Accelerate Delivery Velocity: Leverage AI-assisted development tools (e.g., Cursor, Claude Code) to streamline technical workflows and increase analytical output speed.

As Head of Analytics, youll lead the analytics team and strengthen how data is used to support decision-making across the company. Reporting to the VP of Data & Analytics, youll translate the broader data strategy into clear priorities, high-quality analytical delivery, and measurable business impact.

Youll manage and develop teams of analysts and BI, partner closely with senior stakeholders across Product, Sales, Marketing, Finance, Customer Success, and Operations, and ensure that the company has trusted metrics, actionable insights, and scalable analytical capabilities.

This is a strategic and hands-on leadership role. Youll be expected to set direction, create structure, raise analytical standards, and remain closely involved in the companys most important business questions.

Youre welcome to work in our offices in Tel Aviv, Israel

Your responsibilities will include:

Team leadership and development. Lead, mentor, and develop the analytics team. Set clear expectations, establish ownership, support professional growth, and create a high-performance culture focused on business impact, analytical quality, and accountability.
Analytics strategy execution. Partner with the VP of Data & Analytics to shape the analytics strategy and own its execution, prioritization, and delivery. Translate company goals into a clear analytics roadmap and ensure resources are focused on the highest-impact business needs.
Business partnership. Act as a trusted analytical partner to senior leaders across Product, Sales, Marketing, Finance, Customer Success, and Operations. Understand their objectives, challenge assumptions, and help turn strategic questions into measurable decisions and actions.
Decision support and advanced analysis. Lead high-impact analyses across customer behavior, product performance, revenue, retention, pipeline, operational efficiency, and business growth. Ensure findings are translated into clear recommendations rather than presented as data alone.
Metrics and analytical governance. Establish and maintain consistent KPI definitions, business logic, and analytical standards. Ensure stakeholders use trusted and aligned metrics across dashboards, reports, forecasts, and business reviews.
Dashboard and reporting oversight. Guide the design, implementation, and improvement of executive and operational dashboards. Ensure reporting is relevant, reliable, easy to use, and aligned with business priorities.
Self-service analytics. Enable business teams to access and use data independently while maintaining appropriate governance, security, quality, and consistency. Identify where self-service creates value and where centralized analytical support is required.
AI-driven analytics. Help define and implement AI-assisted analytics capabilities that reduce manual reporting, accelerate insight generation, support natural-language access to data, and proactively surface risks or anomalies. Establish clear quality and validation standards for AI-generated outputs.
Cross-functional data collaboration. Work closely with Data Engineering, Data Architecture, and other technical teams to ensure that analytical datasets, semantic models, and data pipelines support current and future business requirements.
Operating model and prioritization. Build scalable processes for intake, prioritization, delivery, documentation, and stakeholder communication. Balance urgent business requests with strategic initiatives and long-term capability development.

We are looking for a Data Products Engineer to take full ownership of our companys internal product suite - the full-stack applications, AI agent tools, and automation pipelines that power teams across the entire company every day. You will step into an established ecosystem and take the reins. Your mission is to maintain, evolve, and build the next generation of these internal tools so every department can move faster and make smarter, data-driven decisions.
Reporting directly to the VP of CS & Data, this is a high-autonomy, tech-lead role. You wont just write code; you will make architectural decisions, solve complex domain challenges with smart software, and shape how the entire company interacts with data.
How will your day-to-day look?
Own the Internal Product Suite: Lead the development of our core full-stack applications. You will build and scale the central platforms and dashboards that give Product, CS, Sales, and executive leadership visibility into product usage, account health, business performance and more.
Advance the Internal AI Layer: Design, deploy, and refine custom agentic AI workflows - enabling teams across the organization to query complex B2B and product data naturally and conversationally.
Engineer Smart Automations: Architect workflow automations and custom APIs that pipe downstream data directly into the operational tools our teams use every day.
Bridge Data and Software: Partner seamlessly with Data Ops and Data Analysts to transform raw data models into highly usable, intuitive user interfaces and automated actions.
Run the Infrastructure: Own the end-to-end DevOps lifecycle for our internal applications, managing deployment, containerization, observability, and CI/CD pipelines.
Drive Technical Strategy: Act as the technical anchor for internal tools. You will translate high-level product and business challenges from company leaders into shipped, reliable software.

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 Connecteam. 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.

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.