Position Overview
Department: Product
Location: Hybrid – Remote + Office in Washington DC
As a Product Manager at Ordway Labs, you will play a critical role in defining, developing,
and managing all the analytics and reporting needs of Ordway billing and finance platform.
You will collaborate with cross-functional teams to drive product innovation, ensure market
fit, and deliver value to our customers. This role requires a strategic thinker with a strong
understanding of product management principles and a passion for creating exceptional
software solutions.
Job Responsibilities
Product Strategy & Roadmap
- Define and own the analytics product roadmap, aligning it with company data
- strategy and business priorities.
- Translate business intelligence needs into well-scoped, prioritized product
- requirements for dashboards, pipelines, and AI-powered analytics tools.
- Identify opportunities to leverage NLP, LLM-based agents, and intelligent
- automation to improve analytics workflows.
- Drive alignment across stakeholders — from data engineers and architects to
- executives and business unit leads.
Cross-Functional Collaboration
- Serve as the bridge between technical data teams and non-technical business
- stakeholders.
- Partner with Data Governance teams to ensure compliance, security, and data
- quality standards are embedded in product decisions.
- Support go-to-market efforts for analytics tools, including training, enablement, and
- change management.
Delivery & Execution
- Manage the analytics product backlog, running sprint planning, grooming, and
- retrospectives with data and engineering teams.
- Define KPIs and success metrics for all analytics features and track adoption,
- performance, and business impact post-launch.
- Oversee dashboard and visualization delivery, ensuring reports meet
- performance, usability, and governance standards.
- Champion documentation standards for data products, pipelines, and analytics
- architectures.
AI & Intelligent Analytics
- Own the product vision for NLP-based analytics interfaces, conversational BI
- agents, and LLM-powered data tools.
- Define use cases for AI/ML integration — including document understanding,
- anomaly detection, and intelligent automation in analytics workflows.
- Collaborate with engineers to evaluate and integrate LLM-based features into
- existing analytics products (e.g., natural language querying, AI-generated
- summaries).
- Set guardrails for AI-generated insights — defining quality thresholds, evaluation
- metrics, and user-facing explainability requirements.
Discovery & Requirements
- Conduct user research with business analysts, finance, operations, and leadership
- to surface unmet analytics needs.
- Author clear PRDs and user stories that data engineers, BI developers, and
- architects can act on immediately.
- Define acceptance criteria for SQL-driven reports, ETL pipeline outputs, and data
- warehouse deliverables.
- Partner with Analytics Architects to evaluate build-vs-buy decisions for data
- warehouse platforms (Snowflake, ClickHouse, Redshift) and visualization tools
- (Tableau, Power BI, Looker).
Qualifications
Preferred
- Python familiarity — able to read scripts and understand data transformation logic, even if not writing production code.
- Experience with real-time or streaming data products (Kafka, Spark) from a product ownership perspective.
- Familiarity with cloud data platforms (AWS, Azure, GCP) and associated managed analytics services.
- Experience with AI/ML-enabled product features — defining, launching, and evaluating models or LLM-based capabilities in production.
- Exposure to LLM applications (copilots, intelligent search, document understanding) particularly in finance or accounting contexts.
- Background in data governance, compliance, or data quality programs.
- Experience mentoring teams or running a center-of-excellence for analytics best practices.
Required
- 5+ years of product management experience, with at least 2–3 years focused on data, analytics, or BI products.
- Strong SQL literacy — able to read, interpret, and review complex queries; comfortable discussing query optimization and data modeling trade-offs.
- Hands-on familiarity with data warehouse platforms such as Snowflake, Redshift, or ClickHouse.
- Experience managing BI/visualization products — Tableau, Power BI, Looker, or similar.
- Working knowledge of ETL/ELT concepts and data pipeline architectures.
- Demonstrated ability to write PRDs and user stories for data-intensive, technically complex products.
- Experience defining metrics and success criteria for analytics features and data products.
- Strong facilitation and communication skills — ability to run discovery workshops, present roadmaps, and manage stakeholder expectations at all levels.
