Head of Data

Enumerate is looking for an experienced Head of Data to join our team!
We are seeking a dynamic and experienced Head of Data to lead our data strategy, build our infrastructure grow our data team. This role is critical for driving our company's growth through insightful, data-driven decisions. You will be at the forefront of our data initiatives, ensuring that we leverage our data assets to maximize business opportunities and drive innovation.
This is a full-time, salaried position that reports directly to our CFO. This position is remote within the US with the expectation of quarterly travel for team activities. Candidates should be authorized to work in the US without sponsorship.
Who will love this job

• Someone who has a proven track record in building a robust data organization, including talent, tools, processes, and systems, to embed data in strategic decision-making.
• Someone who is a passionate advocate for data integrity, organization, and effective modeling practices.
• Someone who understands the role of data as a key business asset and is skilled in presenting insights that drive impactful decision-making.
• Somone who brings strong technical skills combined with business acumen to identify data-driven trends and maximize opportunities while mitigating risks.

What you’ll do

• Develop a scalable, automated, secure, and auditable data infrastructure to support organizational priorities and decision-making as well as improve operational effectiveness
• Design and implement data operations, governance, analytics, and quality management strategies that support business value and ensure data integrity and security
• Build, scale and lead a robust data engineering team to support the company’s growth trajectory
• Collaborate with other business analysts to align on data operations priorities.
• Work with stakeholders to deliver actionable insights through data analysis and reporting to support informed decision-making and drive customer value
• Ensure the system of record serves as a “single source of truth” for data elements (e.g., GTM stack, customer data, payments data), resolving discrepancies with clear definitions and consistency.
• Promote data literacy across the organization to foster a data-driven culture.
• Define and implement processes for data quality management, including data cleansing, validation, and enrichment.
• Develop and monitor metrics and KPIs to evaluate data operations performance and ensure continuous improvement.
• Partner with cross-functional teams (Sales, Marketing, Finance, Product, Engineering, and Operations) to meet data needs and provide strategic support.
• Work with InfoSec to ensure compliance with data protection regulations (e.g., CCPA, PCI) and implement robust security measures.

You should have

• Extensive hands-on experience in data management, warehousing, governance, quality, and integration, with proficiency in data platforms such as Salesforce, NetSuite, and Boomi.
• Skilled in integrating data from multiple acquired entities.
• Proven ability to manage complex projects, delivering results within scope, time, and budget constraints.
• Strong leadership experience in building and leading high-performing data engineering and analytics teams.
• Expertise in setting data strategies and translating business objectives into actionable data insights.
• Proficient in data analytics, including statistical analysis, data modeling, and visualization, with experience aligning data requirements to business needs.
• Excellent communication skills for engaging stakeholders and translating complex data concepts clearly to cross-functional teams and senior management.
  Committed to continuous learning and staying updated on advancements in data technologies and industry best practices.

Requirements:

• Bachelor's or Master’s in Computer Science, Data Science, Business Analytics, or a related field.
• 5+ years of experience in data science, engineering, or analytics, including 2+ years in a leadership role.
• Proficient with data analytics, CRM, and visualization tools, including Python, R, SQL, Tableau, Power BI, HubSpot, Salesforce, and Google Analytics.
• Experience with big data and cloud-based platforms (e.g., AWS, Google Cloud Platform, Azure).
• Familiarity with machine learning and AI, including NLP, predictive modeling, and both supervised and unsupervised learning.