דרושים Health Data Analyst

• Act as the primary finance partner for marketing organization, providing guidance on budget planning, campaign performance, and efficiency metrics (e.g., CAC, payback, lead funnel metrics).
• Lead and coordinate company-wide ARR and revenue forecasting, annual planning, and rolling forecasts.
• Automate and optimize FP&A tools, processes, and systems to scale with our fast-growing environment.

• 5+ years of experience in FP&A roles, ideally in B2C SaaS or tech.
• Strong understanding of SaaS and marketing performance metrics (ARR, Collection, CAC, LTV).
• Advanced financial modeling and forecasting skills; fluency in Excel and BI platforms.
• Strong interpersonal and communication skills; ability to build trusted relationships with key stakeholders.
• A highly analytical mindset with a hands-on, solution-oriented attitude

• Partner with Product and R&D teams to define success metrics and measure product performance.
• Analyze user journeys, A/B tests, and feature adoption to identify insights that drive growth.
• Build dashboards and reports that make complex data accessible and actionable.
• Collaborate across departments to turn insights into meaningful business and product impact.
• Leverage advanced analytics tools to support an AI-first, data-informed culture.

• 4+ years of experience as a Product Analyst in a web or SaaS company.
• Proven ability to translate complex data into clear narratives and strategic recommendations.
• Strong SQL skills and experience with BI tools (Looker, Tableau, Power BI, etc.).
• Understanding of experimentation methodologies (A/B testing, funnel analysis, etc.).
• Experience with Python, R, or another scripting language - a plus.
• Curiosity, self-motivation, and a passion for learning fast and iterating even faster.

Why you’ll love working here

You’ll find a team that’s driven by data, powered by creativity, and truly cares about its people.

We believe in flexibility, autonomy, and balance - it’s about impact, not hours.

• Technical Leadership & Architecture: Drive data infrastructure strategy and establish standardized patterns for AI/ML workloads, with direct influence on architectural decisions across data and engineering teams
• DataOps Excellence: Create seamless developer experience through self-service capabilities while significantly improving data engineer productivity and pipeline reliability metrics
• Cross-Functional Innovation: Lead collaboration between DevOps, Data Engineering, and ML Operations teams to unify our approach to infrastructure as code and orchestration platforms
• Technology Breadth & Growth: Work across the full DataOps spectrum from pipeline orchestration to AI/ML infrastructure, with clear advancement opportunities as a senior infrastructure engineer
• Strategic Business Impact: Build scalable analytics capabilities that provide direct line of sight between your infrastructure work and business outcomes through reliable, cutting-edge data solutions

• Design Data-Native Cloud Solutions - Design and implement scalable data infrastructure across multiple environments using Kubernetes, orchestration platforms, and IaC to power our AI, ML, and analytics ecosystem
• Define DataOps Technical Strategy - Shape the technical vision and roadmap for our data infrastructure capabilities, aligning DevOps, Data Engineering, and ML teams around common patterns and practices
• Accelerate Data Engineer Experience - Spearhead improvements to data pipeline deployment, monitoring tools, and self-service capabilities that empower data teams to deliver insights faster with higher reliability
• Engineer Robust Data Platforms - Build and optimize infrastructure that supports diverse data workloads from real-time streaming to batch processing, ensuring performance and cost-effectiveness for critical analytics systems
• Drive DataOps Excellence - Collaborate with engineering leaders across data teams, champion modern infrastructure practices, and mentor team members to elevate how we build, deploy, and operate data systems at scale

• 3+ years of hands-on DevOps experience building, shipping, and operating production systems.
• Coding proficiency in at least one language (e.g., Python or TypeScript); able to build production-grade automation and tools.
• Cloud platforms: deep experience with AWS, GCP, or Azure (core services, networking, IAM).
• Kubernetes: strong end-to-end understanding of Kubernetes as a system (routing/networking, scaling, security, observability, upgrades), with proven experience integrating data-centric components (e.g., Kafka, RDS, BigQuery, Aerospike).
• Infrastructure as Code: design and implement infrastructure automation using tools such as Terraform, Pulumi, or CloudFormation (modular code, reusable patterns, pipeline integration).
• GitOps & CI/CD: practical experience implementing pipelines and advanced delivery using tools such as Argo CD / Argo Rollouts, GitHub Actions, or similar.
• Observability: metrics, logs, and traces; actionable alerting and SLOs using tools such as Prometheus, Grafana, ELK/EFK, OpenTelemetry, or similar.

• Data Pipeline Orchestration - Demonstrated success building and optimizing data pipeline deployment using modern tools (Airflow, Prefect, Kubernetes operators) and implementing GitOps practices for data workloads
• Data Engineer Experience Focus - Track record of creating and improving self-service platforms, deployment tools, and monitoring solutions that measurably enhance data engineering team productivity
• Data Infrastructure Deep Knowledge - Extensive experience designing infrastructure for data-intensive workloads including streaming platforms (Kafka, Kinesis), data processing frameworks (Spark, Flink), storage solutions, and comprehensive observability systems

• Relocation support is not available for this position.
• Work visa/immigration sponsorship is not available for this position

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.