Job Overview:

Our Client is seeking a Senior Data Analyst to lead complex, high-impact analytical initiatives that inform business decisions, improve program performance, and support growth. This senior individual contributor will own projects end-to-end—from framing ambiguous questions to building scalable solutions and translating insights into clear, actionable recommendations for stakeholders across the organization.

You will work hands-on with large, varied datasets using Python, Pyspark, and SQL, build and automate analytical workflows on modern cloud platforms (with a strong preference for Databricks), and create repeatable frameworks that elevate team effectiveness. As an informal leader, you will mentor analysts, establish best practices, and help drive planning and execution within a sprint-based environment while connecting analytics to financial goals, client outcomes, and strategic priorities.

Job Responsibilities:

• Own complex analytical projects from problem definition through analysis, recommendation, implementation, and measurement
• Manipulate, analyze, and visualize large datasets using Python, Pyspark, and SQL across formats including JSON, XML, and CSV
• Build and orchestrate scalable, automated analytical workflows using cloud data platforms such as Databricks
• Translate unstructured business questions into clear analytical approaches and actionable recommendations
• Proactively identify performance issues, opportunities, and areas where data can improve business outcomes
• Develop creative solutions and workarounds when product, engineering, or data constraints arise
• Own issues through resolution, coordinating and escalating across teams as needed
• Partner closely with cross-functional stakeholders to understand context, prioritize work, and target highest-value opportunities
• Communicate findings and recommendations through presentations, meetings, documentation, and published analysis
• Manage personal backlog and commitments through two-week sprint planning while contributing to team-level sprints and OKRs
• Lead larger team initiatives, OKRs, planning sessions, and highly collaborative cross-functional meetings when needed
• Create documented best practices, scalable processes, and analytical frameworks that improve team effectiveness
• Mentor junior analysts and serve as an informal leader and escalation point for complex analytical challenges
• Understand key financial goals and optimize program performance against those objectives using data
• Contribute to quarterly and annual forecasting and budgeting by translating operating inputs into financial outcomes
• Develop an understanding of go-to-market strategy and how analytics can support growth
• Incorporate client commitments, revenue, margins, renewals, and potential contractual upside into analyses and recommendations
• Connect analytical work to company objectives, client growth strategies, MBOs, and broader business priorities
• Design solutions that are stable, repeatable, and scalable across teams and programs rather than one-off fixes
• Lead by example, model behaviors aligned with Our Client’s values, and actively participate in broader team and company initiatives

Job Requirements:

• Typically 3–5+ years of relevant analytics experience with demonstrated growth in scope and ownership
• Advanced proficiency with Python, Pyspark, and SQL
• Experience working with complex datasets and multiple structured and semi-structured data formats
• Experience with modern cloud data and analytics platforms; Databricks experience strongly preferred
• Proven ability to define and solve ambiguous or unstructured problems using strong analytical and problem-solving skills
• Demonstrated track record of independently leading complex analytical projects with limited supervision
• Ability to move beyond reporting to identify insights, make recommendations, and influence business decisions
• Strong business acumen with interest in the financial and commercial implications of analytical work
• Excellent written and verbal communication skills for both technical and non-technical audiences
• Strong cross-functional relationship-building skills with the ability to establish credibility across the organization
• Experience mentoring or supporting the development of other analysts is preferred
• Ability to balance multiple priorities and operate effectively in a sprint-based environment.