Sr Data Product Manager

AERIES SOFTWARE LLC • Orange, CA

1d • $145,000 - $175,000 • Remote

About The Position

The Senior Data Product Manager is a strategic product leader who owns the full data analytics and insights ecosystem within the Product Management organization. This role drives the strategy, prioritization, and delivery of modern reporting and analytics capabilities, user behavior insights, and product lifecycle KPI frameworks that enable data-driven decision-making across the organization.

This senior role combines deep expertise in reporting and analytics and AI-assisted tooling with the ability to proactively surface product insights, govern data quality, and influence roadmap priorities. The Sr. Data PM partners closely with engineering, design, business analysts, product managers, and executive stakeholders to ensure the right data reaches the right people at the right time.

This role embraces AI as a force multiplier. From natural language querying and automated insight generation to rapid prototyping and research synthesis, this role will champion a culture of data-informed product development across the team.

Requirements

• 7+ years of hands-on experience with behavioral analytics platforms; direct expertise with Amplitude, Matomo, Mixpanel, Pendo, or equivalent tools in a Product Management role.
• Proven ability to architect and own event tracking frameworks, processing large-scale data volumes with near real-time performance.
• Demonstrated experience building or scaling self-service analytics tools.
• Familiarity with Natural Language Query (NLQ) and AI-assisted analytics concepts, including LLM-powered data exploration interfaces.
• Experience owning data governance practices, including privacy and consent frameworks, data quality standards, and input validation tooling.
• Strong data literacy — comfortable reading and writing SQL, interpreting statistical outputs, and partnering effectively with data engineers.
• Experience with experimentation infrastructure and A/B testing frameworks to support evidence-based product decisions.
• Experience leading measurement strategy for AI-native or LLM-powered product features (intent classification, generative content, Q&A systems, etc.).
• Proficiency with AI productivity tools (Claude, or similar) to accelerate product workflows.
• Experience with structured product discovery frameworks (Opportunity Solution Trees, Jobs-to-Be-Done, Design Sprints, or similar).
• Knowledge of Agile processes and iterative product development.
• Experience building or improving product team processes and operational workflows.
• Clear, concise, and effective written and verbal communication skills, including executive-level reporting and data storytelling.
• Proficiency with modern product management tools, including Azure DevOps, Jira, Aha!, or equivalent.
• Collaborative approach to cross-functional work with a proactive mindset toward identifying and resolving dependencies.
• 5+ years of Product Management experience, with a significant focus on data products, analytics platforms, or business intelligence.
• Demonstrated experience owning a full data platform stack, including analytics, experimentation, customer data platforms, and/or data lake infrastructure.
• Demonstrated experience conducting customer research, product discovery, and prototype-based validation.
• Bachelor's degree in Product Management, Business Administration, Computer Science, Data Science, or a related field — or equivalent work experience.
• Primarily remote; a reliable, distraction-minimized home workspace is expected.
• Must work from one of the following states: AZ, CA, FL, MD, ME, MI, MO, NV, NY, OK, OR, SC, TX, UT, WA, WY
• Prolonged periods of sustained focus during screen and computer-based work
• Ability to travel as required

Nice To Haves

• Background in software engineering, data engineering, or a highly technical discipline is strongly preferred and will be a differentiating factor.
• Experience in B2B SaaS environments; EdTech, enterprise software, or similarly complex product ecosystems a plus.

Responsibilities

• Own the strategy and roadmap for self-service and ad hoc reporting capabilities, enabling internal and external stakeholders to access data without engineering dependency.
• Partner with engineering to deliver scalable, intuitive reporting and analytics tools and ensure reporting infrastructure supports near real-time insights generation.
• Define and maintain reporting standards, data taxonomies, and event tracking frameworks that process high-volume data reliably and consistently.
• Serve as the primary product owner for the user analytics platform, including instrumentation strategy, SDK architecture, and platform governance.
• Drive the roadmap for Natural Language Query (NLQ) capabilities, enabling non-technical stakeholders to explore data through conversational, AI-powered interfaces.
• Lead prioritization of data input validation features to ensure the integrity, completeness, and trustworthiness of all captured behavioral data across products.
• Proactively monitor user behavior trends, session patterns, and funnel analytics to identify friction points, drop-off signals, and areas of product concern and recommend preventative measures.
• Own consent and privacy frameworks governing tracking preferences and data collection across user-facing products.
• Define, document, and maintain KPIs across the full product lifecycle — from discovery and development through launch, adoption, and optimization.
• Build and manage product health dashboards that give leadership, product managers, and cross-functional partners real-time visibility into feature impact and product performance.
• Establish a regular cadence of KPI reviews, executive reporting, and data storytelling that connects product outcomes to business goals.
• Lead measurement strategy for AI-native and LLM-powered features, building evaluation frameworks for intent classification, generative content, and intelligent workflows.
• Use AI tools to accelerate research synthesis, competitive analysis, market landscaping, and opportunity assessment.
• Leverage AI to draft and iterate on product requirements, user stories, acceptance criteria, and stakeholder communications at speed.
• Employ AI-assisted analytics and summarization to rapidly extract insights from user interviews, support tickets, NPS data, and usage telemetry.
• Evaluate and recommend emerging AI/ML capabilities for integration into the product platform to automate workflows, improve data quality, and enhance user experience.
• Champion AI literacy within the product team — sharing tools, techniques, and workflows that raise team velocity and output quality.
• Lead continuous discovery through user interviews, usability testing, contextual inquiry, and prototype feedback sessions to validate product directions before committing engineering resources.
• Develop testable hypotheses and run structured experiments to drive evidence-based product decisions grounded in behavioral data.
• Build rapid prototypes and interactive concept demos using AI prototyping tools (Lovable, Figma) to make data and analytics ideas tangible early in the discovery cycle.
• Continuously synthesize customer needs, data trends, and business goals to maintain an outcome-oriented data and insights roadmap.
• Use structured prioritization frameworks to make transparent trade-off decisions across NLQ, validation, reporting, and KPI initiatives.
• Identify integration opportunities that improve data interoperability, unify workflows, and create measurable value across the product portfolio.
• Partner with engineering, business development, and leadership to define integration roadmaps that balance speed-to-value with technical feasibility.
• Collaborate with design and business analysts to craft appropriate solutions to validated data and insight problems.
• Partner with Marketing, Sales, Customer Success, and Support to surface actionable insights and align on go-to-market readiness.
• Maintain a closed feedback loop with Customer Success to ensure post-launch learnings and customer data signals flow back into discovery and roadmap planning.
• Establish and maintain standardized workflows, templates, and processes for data product development that improve cross-functional efficiency.
• Own and optimize the analytics and product tooling stack, ensuring adoption and integration across the product team.
• Build and maintain dashboards that surface product performance data, customer feedback trends, and discovery insights to leadership.

Benefits

• Health insurance coverage for employees and covered dependents
• Health Savings Account with employer contributions
• 401(k) plan with up to 4% employer match
• “Responsible PTO” with additional paid time off for sick time, volunteering, bereavement, and jury duty
• 11 paid holidays with additional paid closure between Dec 26–Jan 1
• Educational Reimbursement program and opportunities for ongoing professional development

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 11-50 employees