דרושים » ניהול ביניים » Data Platform Team Lead

Were looking for an experienced and passionate Staff Data Engineer to join our Data Platform group in TLV as a Tech Lead. As the Groups Tech Lead, youll shape and implement the technical vision and architecture while staying hands-on across three specialized teams: Data Engineering Infra, Machine Learning Platform, and Data Warehouse Engineering, forming the backbone of data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives toward becoming the most precise and efficient insurance company on the planet. By embracing Data Mesh principles, we create tools that empower teams to own their data while leveraging a robust, self-serve data infrastructure. This approach enables Data Scientists, Analysts, Backend Engineers, and other stakeholders to seamlessly access, analyze, and innovate with reliable, well-modeled, and queryable data, at scale.
In this role youll :
Technically lead the group by shaping the architecture, guiding design decisions, and ensuring the technical excellence of the Data Platforms three teams
Design and implement data solutions that address both applicative needs and data analysis requirements, creating scalable and efficient access to actionable insights
Drive initiatives in Data Engineering Infra, including building robust ingestion layers, managing streaming ETLs, and guaranteeing data quality, compliance, and platform performance
Develop and maintain the Data Warehouse, integrating data from various sources for optimized querying, analysis, and persistence, supporting informed decision-makingLeverage data modeling and transformations to structure, cleanse, and integrate data, enabling efficient retrieval and strategic insights
Build and enhance the Machine Learning Platform, delivering infrastructure and tools that streamline the work of Data Scientists, enabling them to focus on developing models while benefiting from automation for production deployment, maintenance, and improvements. Support cutting-edge use cases like feature stores, real-time models, point-in-time (PIT) data retrieval, and telematics-based solutions
Collaborate closely with other Staff Engineers across to align on cross-organizational initiatives and technical strategies
Work seamlessly with Data Engineers, Data Scientists, Analysts, Backend Engineers, and Product Managers to deliver impactful solutions
Share knowledge, mentor team members, and champion engineering standards and technical excellence across the organization

We are building the next generation of digital heart-health products and our data platform is the foundation.
Were looking for a Data Platform Team Lead to own and evolve an AI-first, cloud-native data platform that already:
Serves 100+ data users across the company
Powers ML models impacting thousands of users every day
Supports production systems in a company that literally saves lives
You will lead a growing team of 4 data engineers and 1 BI developer, and work in close, day-to-day partnership with Product, Analytics, Data Science & Engineering
Our future is serving millions of users across multiple products in the heart-health ecosystem. This role owns the platform that will scale us there. We are intentionally building an AI-first / agentic data platform.
That means:
Automating table creation, validation, and testing
Agent-driven monitoring for data quality, freshness, and failures
Using agents to generate and maintain documentation
Reducing manual operational overhead so humans focus on architecture, leverage, and product impact
You will have full organizational support to rethink how a modern data platform should work in an AI-native environment, not incremental improvements, but fundamental design decisions.
Our Technologies stack: Python, Spark, Airflow, DBT, Kafka, AWS (Glue, EMR, S3, Athena and more), Snowflake, Docker, Kubernetes, MongoDB, Redis, Postgres, Elasticsearch, and evolving
Responsibilities:
Platform Leadership & Team Management: Lead, mentor, and grow a team of senior data engineers and BI developers. Set a high bar for technical quality, ownership, and delivery.
Core Data Platform Architecture: Own the design, evolution, and reliability of our cloud-native data platform, balancing scalability, cost, security, and developer velocity.
Deep Collaboration with R&D: Work closely with product, engineering, and ML teams to ensure the data platform enables fast experimentation, production ML, and new product development.
Production-Grade Data Systems: Oversee end-to-end data pipelines, streaming and batch processing, semantic layers, and analytics foundations that serve the entire organization.
Operational Excellence: Ensure data quality, freshness, observability, and incident response meet the standards of a mission-critical system.

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.