Lead Data Insights Analyst (SQL, Root Cause Analysis, Stakeholder-Facing)

pureIntegration•Reston, VA

21h•Remote

About The Position

We are looking for a hands-on Analytics Lead who can go beyond “what happened” and uncover why it happened and what should be done next. In this role, you will work with large-scale operational data to identify drivers of key trends, generate actionable insights, and guide business decisions. You will also lead a small team of analysts, ensuring high-quality, accurate, and impactful analysis. This is a high-visibility, stakeholder-facing role requiring strong communication, structured thinking, and the ability to influence outcomes. This is a fully remote, W-2 hourly contract role (6–9 months) that requires frequent travel to client locations across the U.S.

Requirements

7–10+ years of experience in data analysis, advanced analytics, data science, or a related field.
Bachelor’s degree in Engineering, Computer Science, Statistics, Mathematics, Information Systems, or a related discipline, or equivalent professional experience.
Strong experience in data analysis focused on insights (not just reporting)
Expertise in SQL (complex queries, joins, aggregations)
Advanced Excel skills (pivot tables, data manipulation)
Proven experience performing: Root cause analysis, Trend/driver analysis, Hypothesis-based problem solving
Experience presenting insights to business stakeholders/leadership.
Strong communication and storytelling skills

Nice To Haves

Experience with Tableau or MicroStrategy.
Experience working with large datasets (e.g., Redshift, data warehouses).
Telecom, operations, or customer behavior analytics experience.
Experience leading or mentoring analysts.
Candidates who can interpret data and influence decisions.

Responsibilities

Lead end-to-end analytical investigations to answer business questions such as: Why did key metrics change? What are the drivers behind customer or operational trends?
Perform deep-dive, hypothesis-driven analysis using SQL and Excel.
Identify root causes using segmentation, trend analysis, and comparative analysis.
Translate complex data into clear, actionable insights for leadership.
Create high-quality deliverables (PowerPoint, summaries, recommendations).
Partner with business and technical stakeholders to validate findings.
Manage and mentor a team of analysts (delegation, QA, prioritization).
Ensure accuracy through data validation, reconciliation, and quality checks.
Drive structured problem-solving and analytical rigor across the team.