Senior Technical Product Manager (IL) - Matia

Experience:5+ years as a Product Manager, with at least 2 years on data-intensive or infrastructure products (data pipelines, databases, observability, analytics platforms, developer tools). Data Modeling Fluency:Deep understanding of data modeling principles, schema design tradeoffs, and how modeling decisions ripple downstream into pipelines and consumers. Database Depth:Genuine working knowledge of relational database internals, especially Postgres and MySQL: replication mechanisms, change data capture, transaction logs, and performance characteristics. Technical Fluency:Strong SQL, comfort reasoning about data quality (freshness, completeness, lineage), and the ability to engage deeply with engineers on tradeoffs. Execution Track Record:Demonstrated success shipping technical products end-to-end, from discovery through delivery with clear metrics moved. Remote Reporting Effectiveness:Comfortable operating with a manager based in a different country and time zone. Writing-first, proactive, high independence. Startup DNA:Hungry. Thrives in hectic, resource-constrained environments. Able to work with ambiguity and act autonomously. AI Productivity:Skilled at using modern AI tools to accelerate product workflows and increase day-to-day velocity. Software Engineering Background:Prior hands-on experience as a software engineer, data engineer, or DBA is a significant advantage, particularly for reasoning about data modeling and pipeline architecture. Experience at a data integration, data movement, or data observability company (e.g., Fivetran, Airbyte, Hightouch, Monte Carlo, or similar). Experience as the first or early PM at a startup.

Own Product Areas Across the Platform:Take end-to-end ownership of product areas spanning Ingestion, Reverse ETL, Observability, and Catalog, translating complex technical and data challenges into clear priorities, crisp specifications, and measurable outcomes. Go Deep on Data Modeling and Infrastructure:Reason fluently about data modeling, schema design, and pipeline internals, including Postgres WAL and logical decoding, MySQL binlog, CDC edge cases, sync performance, and schema evolution, and turn that depth into better product decisions. Partner with Engineering Side by Side:Work in person, day to day, with our Tel Aviv engineering team to deep dive into problems, unblock delivery, and move fast on high-quality outcomes. Manage a Remote Reporting Relationship:Keep the VP of Product in New York aligned through clear written specs, proactive updates, and strong async communication, operating with real independence between syncs. Be the Voice of Customers:Speak regularly with customers to uncover pain points, validate product direction, and ensure what we build resonates with real-world data teams. Iterate and Prioritize Ruthlessly:Continuously refine the roadmap based on data, user feedback, and results. Make tough tradeoffs and cut scope when needed to ship faster and learn sooner. Run Tight Feedback Loops:Define and track product metrics, run experiments, and follow through post-launch to confirm outcomes. Know the Competitive Landscape:Develop a sharp point of view on the data integration and observability market, and use it to inform positioning and prioritization. Shape Product Culture:Help establish Matia's product rituals and standards, from specs and prioritization frameworks to how we define success and learn from customers.

Experience:5+ years as a Product Manager, with at least 2 years on data-intensive or infrastructure products (data pipelines, databases, observability, analytics platforms, developer tools). Data Modeling Fluency:Deep understanding of data modeling principles, schema design tradeoffs, and how modeling decisions ripple downstream into pipelines and consumers. Database Depth:Genuine working knowledge of relational database internals, especially Postgres and MySQL: replication mechanisms, change data capture, transaction logs, and performance characteristics. Technical Fluency:Strong SQL, comfort reasoning about data quality (freshness, completeness, lineage), and the ability to engage deeply with engineers on tradeoffs. Execution Track Record:Demonstrated success shipping technical products end-to-end, from discovery through delivery with clear metrics moved. Remote Reporting Effectiveness:Comfortable operating with a manager based in a different country and time zone. Writing-first, proactive, high independence. Startup DNA:Hungry. Thrives in hectic, resource-constrained environments. Able to work with ambiguity and act autonomously. AI Productivity:Skilled at using modern AI tools to accelerate product workflows and increase day-to-day velocity. Software Engineering Background:Prior hands-on experience as a software engineer, data engineer, or DBA is a significant advantage, particularly for reasoning about data modeling and pipeline architecture. Experience at a data integration, data movement, or data observability company (e.g., Fivetran, Airbyte, Hightouch, Monte Carlo, or similar). Experience as the first or early PM at a startup.