Director of Data

The Director of Data at GiveDirectly is responsible for leading the data infrastructure, strategy, and analytics function. This involves developing the data lakehouse, automating data quality checks, and providing insights through KPI reviews. The director collaborates with leaders across the organization to ensure that data and insights drive high-impact decisions for improving recipient outcomes and operational efficiency.

Candidates for the Director of Data position at GiveDirectly should possess a minimum of 8 years of relevant experience in data engineering, analytics, or data science, along with at least 4 years of people management experience. Strong analytical skills, proficiency in SQL and Python, and experience with modern data stack tools such as Databricks and Tableau are critical for success in this role.

The Director of Data plays a crucial role in organizational decision-making at GiveDirectly by developing insights from data that inform strategic discussions and help prioritize initiatives. By establishing a culture of rigorous data-driven decision-making, the director ensures that the insights generated by the data team are effectively utilized across the organization.

The work environment for the Director of Data at GiveDirectly is supportive and dynamic, emphasizing collaboration, inclusivity, and professional growth. As a fully remote position, it allows for flexibility while fostering an atmosphere where team members from diverse backgrounds can thrive and grow. The organization strongly encourages feedback and engagement among its staff members.

The Director of Data at GiveDirectly will work with a modern tech stack, including tools such as Spark, Databricks, AWS, Salesforce, and Tableau. Familiarity with these technologies is essential to effectively oversee the data infrastructure and analytics functions, ensuring scalability, reliability, and security.

In responding to this question, focus on specific projects you've led or contributed to in data engineering. Highlight the importance of building robust data infrastructure as it directly impacts the quality and reliability of the insights generated for organizational decision-making.

Demonstrate your ability to foster collaboration by discussing experiences where you successfully aligned your data team's objectives with the broader organizational goals. Share examples of how you communicated with stakeholders to ensure shared understanding and prioritization of initiatives.

To address this question, describe various strategies you've employed to enhance data quality, such as implementing automated checks, fostering a culture of accountability among data producers, and regular audits. Be sure to emphasize the continuous improvement aspect of data governance.

Share an example of a situation where you navigated conflicting priorities. Emphasize your communication skills, ability to facilitate discussions, and how you worked towards a mutually beneficial resolution while maintaining focus on the organization's strategic objectives.

Discuss your proficiency with various data visualization tools like Tableau or Power BI, and explain how you would apply them to create impactful dashboards that provide transparency and insight into performance metrics for various departments at GiveDirectly.

When answering this, give a brief overview of a project from inception to impact, highlighting the challenges you faced, your role in overcoming them, and the measurable outcomes as a result of your data-driven approach.

Focus on your process for translating data into strategic insights. Discuss how you engage with business leaders to understand their needs and ensure that your team's deliverables align with their objectives, emphasizing a feedback loop to refine and enhance future insights.

Describe your strategies for promoting data literacy and empowering teams to harness data insights in their day-to-day work. Include examples of training sessions, workshops, or tools you've implemented to encourage a data-first mindset.

Speak to your background with machine learning, discussing projects where you've applied these principles to solve business problems. Highlight your understanding of algorithms, model evaluation, and how you've used predictive analytics to drive decisions.

Share your strategies for continuous learning in the data field, including industry publications, online courses, networking with peers, and attending conferences. Emphasize your commitment to integrating new knowledge into your work to maintain a competitive edge.