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Were looking for a BI & Data Engineering Team Lead to join our BI team and take end-to-end ownership of high-impact analytics foundations while mentoring a team of 4-6 talented BI Data Engineers. This role sits at the core of how measures success, makes decisions, and scales-turning raw data into trusted, business-critical insights used across Product, GTM, and Finance.
In this role, you'll combine people leadership with hands-on technical depth (roughly 30% of your time), owning the roadmap, architecture, and delivery of BI platform. Youll shape how AI and agentic workflows transform the way BI is built and consumed, helping raise the bar for analytics engineering across the company.
Hands-on experience using GenAI to improve analytics engineering workflows, automate development processes, and increase delivery speed is a must for this role.
This role is based in Tel Aviv. We work in a hybrid model, with 3 days a week in the office.

You and your team will work primarily with dbt, BigQuery, Looker, and GitHub, while using AI-enabled tools such as Cursor, MCP integrations, n8n, and OpenClaw to automate workflows and scale how the team works.

Success in this role requires strong leadership, technical depth, business understanding, and the ability to turn complex data into clear, actionable recommendations.

Key Responsibilities
Lead, manage, and develop a team of Data Analysts, including setting goals, providing feedback, and supporting their professional growth.
Own the teams priorities and analytical roadmap, ensuring the team focuses on the highest-impact business needs.
Define and drive technical and analytical standards across data modeling, SQL, dbt, testing, code reviews, and BI.
Partner with stakeholders and senior leadership to understand business needs, define KPIs, and translate data into actionable recommendations.
Lead high-impact analyses and guide the development of reliable, scalable data models and Looker dashboards.
Ensure data quality and lead investigations into anomalies, tracking issues, and inconsistent metrics.
Drive AI-native ways of working by turning repeatable analyses and processes into reusable, automated workflows.
Stay hands-on with data, code, and analysis when tackling complex or high-impact problems.

We are looking for a strategic product leader to head our Data Platform domain - a core area of our offering. This role is critical to the companys growth, driving both short-term impact and long-term vision for managing and leveraging massive amounts of structured and unstructured clinical data. In this role, you will lead the product strategy and execution for the domain, while guiding and mentoring product managers within the team. You will work closely with Engineering, Data Science, Clinical Experts, the rest of the Product group, as well as partners and strategic customers, shaping how our platform operates and scales to meet the needs of our growing business.

Responsibilities
Define and drive the roadmap for our Data Platform, balancing short-term business needs with long-term scalability and platform strategy.
Own the product vision for data ingestion, processing, and access, ensuring the platform supports all product groups and business initiatives.
Lead and mentor a team of product managers, fostering growth, collaboration, and a culture of ownership and impact.
Support your team in translating complex technical and data requirements into clear product specifications, prioritizing initiatives that maximize business impact.
Partner closely with Engineering, Data Science, Clinical Experts, Customer Success, the entire PM group, and external partners and strategic clients, to design and prioritize initiatives, ensuring data quality, performance, and usability.
Drive cross-team technical initiatives end-to-end, coordinating dependencies and aligning stakeholders across the organization.
Establish key metrics to measure platform performance, adoption, and impact on product outcomes.

we are looking for a Data Infrastructure Lead.
As the Data Infrastructure Lead, you will own the technical direction, architecture, and delivery of Skais core production data infrastructure (MySQL, SingleStore, Snowflake, Airflow, and Microservices).
In this role, you will balance in-house, open-source, and SaaS solutions to manage petabyte-scale data while ensuring system reliability, scalability, and cost-efficiency. You will blend hands-on engineering, technical architecture, vendor management, and team mentorship. You will lead cross-functional delivery, drive operational excellence across a 24/7 production environment, and set engineering guardrails for cloud-based data systems across the company.
Responsibilities:
Technical Leadership & Architecture: Set engineering guardrails, lead architectural reviews, lead the pods daily, and balance design tradeoffs for cloud-based data systems across all business units.
Execution & Delivery: Own the pods Scrum processes (epics, stories, tracking), balance technical debt management with rapid feature delivery, and drive multi-project execution.
Hands-on Engineering & Escalations: Stay active in code and infrastructure, serving as the primary technical escalation point for complex, 24/7 production issues.
Ops, High Availability & Reliability: Oversee operational readiness, rotation schedules, high availability (HA), backup and recovery processes, and automation to maintain 24/7 production uptime.
Mentorship & Team Culture: Raise the technical bar, foster a culture of engineering excellence, mentor team members, and drive professional growth within the pod.
Stakeholder & Vendor Alignment: Act as a strategic partner to align roadmap planning, bridge technical execution with business goals, and serve as the main point of contact for data infrastructure vendors.

we are looking for a Data Platform Engineering Team Leader
As a Data Platform Engineering Team Leader on the Infrastructure R&D Department in our Tel Aviv office, youll lead the engineering team behind the data platform powering reporting, billing, experimentation, ML training, and revenue optimization.
Youll shape the technical direction of one of our most critical platforms, grow exceptional engineers, and solve complex data infrastructure challenges at massive scale-building systems that are reliable, scalable, and easy to use.