TL;DR

Staff Product Manager (Data Platform): Defining and executing the data ecosystem vision for %hirify_global%'s Trust and Safety Platform, with an accent on enabling self-service data consumption across the organization. Focus on bridging the gap between Data and Risk analysts, Data Engineering, Data Science, and business units, ensuring high-quality, discoverable data assets and shaping core data infrastructure.

Location: Petach Tikva, Israel

Company

%hirify_global% is a global financial technology platform powering prosperity for approximately 100 million customers worldwide with products like TurboTax, Credit Karma, QuickBooks, and Mailchimp.

What you will do

Define and champion the product vision and roadmap for data products (e.g., internal analytics platforms, external data APIs, machine learning model outputs, core data pipelines).
Serve as primary liaison between data scientists, data engineers, software engineers, and business stakeholders to gather requirements and prioritize features.
Translate complex business problems and user needs into clear, actionable user stories and functional specifications for data products.
Design and optimize data products to maximize self-service consumption, including curating accessible datasets, developing %hirify_global%ive interfaces, and ensuring documentation.
Drive the adoption, feature roadmap, and success of core data services to empower analysts and business users.
Manage the backlog for data product development, making trade-off decisions based on business impact, technical feasibility, and strategic alignment.

Requirements

5+ years of product management experience, with at least 3 years specifically managing data products, data platforms, or analytics tools
2+ years of hands-on experience with Intermediate SQL and analytics skills
Understanding of NoSQL methodology, data modeling, and ML models.
Demonstrated expertise in Self-Service tools and a proven ability to increase data literacy and drive tool adoption.
Strong technical fluency in the data domain, including public cloud service providers (AWS, Azure, GCP), data warehousing tools (Snowflake, BigQuery, Redshift), Big Data Processing Frameworks (Apache Spark, DataBricks), ETL/ELT processes and data pipelines (Airflow, DBT), data governance, quality, and security principles.
Understanding of streaming architecture and fluency in GDPR / CCPA / 7216 restrictions regulations.

Culture & Benefits

Competitive compensation package with a strong pay for performance rewards approach.
Eligibility for a cash bonus, equity rewards and benefits in accordance with applicable plans and programs.
Commitment to fair pay, with regular comparisons across categories of ethnicity and gender.