Director of Data Strategy & Analytics

Key Responsibilities

Key ResponsibilitiesData Strategy & Vision
• Define and own the company’s multi-year data strategy, ensuring alignment with business priorities across revenue growth, operational efficiency, and customer experience.
• Develop and maintain enterprise data standards, governance frameworks, and policies that ensure consistency, accuracy, and compliance across all data assets.
• Identify and evaluate emerging data technologies, platforms, and methodologies — including AI/ML-powered analytics — and build a roadmap for their adoption where they deliver measurable commercial value.
• Partner with senior leadership (VP Finance, CTO, SVP Operations) to translate business questions into structured analytical programs w/clear data requirements & success metrics.
• Represent the data function in cross-functional leadership discussions, board presentations, and external partner conversations as the company’s data authority.
Data Infrastructure & Engineering
• Oversee the design, development, and continuous improvement of our data pipelines, data warehouse, and ETL/ELT processes to ensure scalable, reliable, and timely data delivery.
• Deploy and manage automation tools that streamline the acquisition, processing, and integration of structured and unstructured data from disparate internal and external sources.
• Establish and enforce data quality standards and monitoring practices — implementing data validation, lineage tracking, and anomaly detection to safeguard the integrity of all data assets.
• Evaluate and manage key data platform vendors and tools (e.g., cloud data warehouses, BI platforms, statistical software), ensuring fit-for-purpose selection and cost-effective usage.
• Ensure data infrastructure is built for scale, with architectural decisions that support 2–3x data volume growth over the next 18–24 months.
Analytics, Insights & Business Intelligence
• Lead the design and delivery of dashboards, reports, and analytical models that support decision-making across commercial, operational, and financial functions.
• Construct and maintain analytical datasets that enable trend analysis, forecasting, cohort analysis, segmentation, and performance benchmarking across the business.
• Apply statistical methods, predictive modeling, and advanced analytical methodologies to surface non-obvious insights that inform both tactical decisions and long-term strategy.
• Champion self-serve analytics capabilities, enabling business stakeholders to access and interpret data independently while maintaining appropriate governance guardrails.
• Develop a rigorous A/B testing and experimentation framework to support continuous improvement across product, pricing, marketing, and customer success functions.
Team Leadership & Organizational Development
• Build, lead, and develop a high-performing data team — including analysts, and BI developers — through hiring, mentorship, performance management, and structured growth planning.
• Establish a team culture defined by intellectual curiosity, data literacy, operational discipline, and a strong bias toward delivering business impact.
• Create a data literacy program that upskills non-technical stakeholders across the organization, fostering a data-informed culture at every level.
• Own departmental budgeting, headcount planning, and vendor spend, ensuring resources are deployed effectively to maximize the return on data investment.
• Define and track team performance metrics — including delivery velocity, data quality scores, stakeholder satisfaction, and coverage of analytical use cases.
Stakeholder Partnership & Data Activation
• Act as a strategic thought partner to commercial and operational leaders, translating complex analytical outputs into clear, actionable recommendations.
• Partner with the Sales and Marketing teams to develop customer segmentation models, demand forecasting tools, and campaign attribution frameworks that directly support revenue growth.
• Support the Finance function with financial modeling inputs, scenario analysis, and KPI reporting that improve the accuracy and speed of financial planning cycles.
• Collaborate with Product and Technology teams to embed data-driven feedback loops into the product development lifecycle, from feature prioritization to post-launch measurement.
• Develop and maintain a stakeholder engagement cadence — including regular business reviews, roadmap alignment sessions, and feedback mechanisms — to ensure the data function remains tightly connected to evolving business needs.
Data Governance, Security & Compliance
• Own the company’s data governance framework, ensuring policies and practices are in place for data classification, access control, retention, and documentation.
• Ensure all data practices are compliant with applicable data privacy regulations (e.g., GDPR, CCPA) and internal security standards, particularly in relation to customer and partner data.
• Develop and maintain a data catalog and data dictionary that provides organization-wide visibility into available data assets, their provenance, and appropriate use.
• Proactively assess and mitigate data risk, including risks associated with third-party data sharing, AI model inputs, and evolving regulatory requirements.

What You’ll Own (Key Metrics)

What You’ll Own (Key Metrics)
• Data platform uptime, pipeline reliability, and data freshness SLAs across all critical datasets
• Analytical coverage: percentage of key business decisions supported by structured data and reporting
• Data quality score across core data domains (customers, transactions, product, supplier)
• Time-to-insight: average time from data request to stakeholder-ready output
• Self-serve analytics adoption rate across non-technical business stakeholders
• Team engagement, retention, and skills development progress within the data function
• Data infrastructure cost as a percentage of revenue
• Number of active analytical initiatives and conversion rate from insight to business decision

What Success Looks Like Over the Next 12 Months

What Success Looks Like Over the Next 12 Months

Within the first 90 days, you will complete a comprehensive audit of our existing data infrastructure, tooling, team capabilities, and analytical coverage — and deliver a prioritized data strategy roadmap to the executive team. This roadmap will identify the top five highest-ROI data initiatives to pursue across commercial/finance intelligence, operational analytics, and data quality improvement.

By month six, at least three of those initiatives will be in flight with clear owners, timelines, and success metrics. The team will have measurably improved data reliability and stakeholder satisfaction, and at least one new analytical capability — a forecasting model, a segmentation framework, or a self-serve dashboard suite — will be live and actively used by the business.

By end of year one, Purchasing Platform will have a defensible, scalable data infrastructure; a mature governance framework; a culture of data-informed decision-making across the full organization; and a data function that is regarded internally as a strategic asset rather than a reporting service.

What We’re Looking For

What We’re Looking ForExperience & Qualifications

• 7+ years of progressive experience in data analytics, business intelligence, or data engineering, with at least 3–5 years in a leadership or management capacity.
• Proven experience in a B2B eCommerce, marketplace, or B2B SaaS environment with annual revenue of $20M+; experience scaling a data function through a high-growth phase is strongly preferred.
• Demonstrated success building and leading data teams, including hiring, developing, and retaining analytical talent.
• Strong hands-on proficiency with SQL and at least one statistical or data science language (Python, R); experience with modern data stack components (e.g., dbt, Snowflake, BigQuery, Redshift, Fivetran, Airflow).
• Deep experience with business intelligence and data visualization platforms (e.g., Tableau, Looker, Power BI) and a track record of building dashboards and reporting frameworks that drive commercial action.
• Experience with statistical modeling, forecasting techniques, and A/B testing methodologies.
• Familiarity with data governance frameworks, data privacy regulations (GDPR, CCPA), and enterprise data security best practices.
Core Competencies

Data Quality  |  Data Visualization  |  Statistical Analysis  |  Forecasting  |  Trend Analysis  |  Data Governance  |  Team Building  |  Stakeholder Communication  |  Data Standards  |  Statistical Software  |  BI Platforms  |  Budget Management

Managerial Scope

Staffing  |  Pay Decisions  |  Training & Development  |  Performance Evaluation  |  Day-to-Day Supervision  |  Budget Ownership  |  Process & Policy Development (Partial)

Culture Fit

Culture Fit

This role is best suited to a leader who is genuinely energized by the challenge of turning raw data into competitive advantage. You are as comfortable getting into the details of a broken pipeline as you are presenting a data strategy to the executive team — and you bring intellectual rigor and pragmatic judgment to both.

You lead with curiosity, communicate with clarity, and find satisfaction in building the people and systems around you. You understand that the most sophisticated model in the world has no value if it doesn’t change a decision — and you hold yourself and your team accountable to business impact, not just technical output.

At this stage of growth, the Director of Data Strategy & Analytics must be comfortable operating with some ambiguity, making decisions with imperfect information, and course-correcting quickly. We don’t expect perfection from our analytical work. We expect speed and a relentless focus on delivering insight that drives the business forward. Bring it.