What Findem is:
Findem is the only talent data platform that combines 3D data with AI. It automates and consolidates top-of-funnel activities across your entire talent ecosystem, bringing together sourcing, CRM, and analytics into one place. Only 3D data connects people and company data over time - making an individual’s entire career instantly accessible in a single click, removing the guesswork, and unlocking insights about the market and your competition no one else can. Powered by 3D data, Findem’s automated workflows across the talent lifecycle are the ultimate competitive advantage. Enabling talent teams to deliver continuous pipelines of top, diverse candidates while creating better talent experiences, Findem transforms how companies plan, hire, and manage talent. Learn more at www.findem.ai
Why we need you:
We're seeking a Data Product Manager who is an organizational force with a proven track record in structuring large projects and facilitating cadenced communications across a Data Engineering group.
This role will be crucial in keeping projects on track and increasing visibility across the entire organization to keep our Data Engineering team laser-focused on the most high-value projects. Data is at the heart of our product. Our unique 3D data empowers customers to make informed decisions that surpass the capabilities of traditional keyword searches.
You will be responsible for ensuring up-to-date documentation, implementing processes and rituals, and triaging requests from internal and external stakeholders. As you become more familiar with the data and systems you will become a thought partner for your counterparts and colleagues in Product, Design, Engineering, and GTM.
In this role, you will become a trusted advisor for stakeholders regarding the data at Findem. Our customer base ranges from small, founder-operated start-ups to Fortune 500 global enterprises. By joining our data team, you will play a pivotal role in driving innovations, helping our customers unlock the full potential of 3D data for more informed and effective decision-making.
What you’ll be doing:
- Sharing ownership of outcomes with Engineering and taking complete accountability when updates are not communicated or deadlines are missed
- Proactively take initiative to plan and lead Backlog / Sprint planning meetings, structuring and implementing SDLC along with rigorous testing plans
- Writing well-scoped tickets and user stories including definitions of done
- Coordinating documentation in the general knowledge base (SLAs/SLOs, Privacy/Regulatory requirements) and reminding owners to follow through
- Defining metrics necessary for product success in conjunction with Engineering and Leadership
- Triaging internal requests and instituting processes to research, track, and complete with follow-up with stakeholders
- Working partial US West Coast hours, meaning available 9a-noon Pacific time four days a week
What you have:
- 4+ years of experience building and improving data assets at a SaaS company (gathering requirements, creating user stories, and developing product roadmaps)
- 2+ years of experience working on large-scale data engineering projects as a product manager on enterprise-level data platforms
- Above average ability to understand & articulate the ROI of any basic requirement or project and capture it in release notes
- Experience categorizing issues into root cause components (e.g., data freshness vs accuracy)
- Experience with project management tools (Jira a plus)
- Ability to thrive in a chaotic environment and perform without a lot of detailed guidance
- Experience working with NoSQL databases
- Strong interpersonal skills and ability to build rapport with stakeholders and communicate effectively across all levels of the organization
- Proficient with spreadsheets (e.g., Microsoft Excel, Google Sheets)
- Ability to increase transparency without increasing uncertainty
- Exposure to Product Strategy, Prioritization, and Vision a plus
- Exposure to User Research and Requirements Gathering a plus
- Exposure to Market/Competitive Analysis a plus
