Job
Description
Here's a comprehensive description and job description (JD) for a Data Analyst Lead role, suitable for a growth-oriented organizationespecially in tech, product, or edtech environments: Role: Data Analyst Lead Role Overview We are seeking a Data Analyst Lead who will take ownership of our analytics strategy, leading a team of analysts and working closely with stakeholders across product, marketing, operations, and engineering. The ideal candidate is not only strong in SQL, data modeling, and visualization but also highly business-savvycapable of turning data into actionable insights that drive growth and efficiency. You will be responsible for building scalable dashboards, running deep-dive analyses, mentoring junior analysts, and enabling data-driven decisions across the company. Key Responsibilities Lead & Mentor : Manage a small team of data analysts. Set direction, review work, provide mentorship, and grow team capabilities. Business Partnering : Collaborate with stakeholders across product, marketing, sales, finance, and ops to understand their data needs and translate them into impactful analytics projects. Data Strategy : Define and drive data quality, consistency, and accessibility across departments. Build scalable data pipelines in collaboration with engineering teams if needed. Analysis & Reporting : Design, implement, and maintain dashboards (using tools like QuickSight, Metabase). Perform exploratory data analysis (EDA), cohort analysis, funnel drop-off analysis, retention modeling, etc. Provide insights on KPIs like customer acquisition cost (CAC), LTV, churn, NPS, and usage metrics. Experimentation : Support A/B testing strategies by defining metrics, evaluating results, and communicating outcomes clearly. Drive Insights : Proactively identify business trends, anomalies, and opportunities for growth or efficiency using data. Tools & Tech : Oversee adoption of BI tools, ensure SQL standards, and guide best practices in dashboard design and analytics workflows. Requirements Must-Have 5+ years of experience in analytics, with at least 1–2 years leading a team or cross-functional projects. Advanced SQL skills and experience working with large datasets (PostgreSQL, Redshift, etc.). Strong skills in dashboarding and visualization (Quicksight, Metabase). Experience with statistical or data modeling tools (Python, R, or similar). Proven experience in designing KPIs and performance dashboards across teams. Business acumen and the ability to convert ambiguous problems into clear data-backed narratives. Nice-to-Have Experience in a high-growth startup or tech/edtech environment. Exposure to data warehousing (e.g., AWS Glue, Redshift, Snowflake). Familiarity with experimentation frameworks or product analytics tools (Mixpanel, Amplitude, GA4). Understanding of data privacy and governance best practices.
