Senior Data Analyst

Job description

A leading organization is seeking a Senior Data Analyst to support complex business and pharmacy benefits initiatives through hands-on data analysis, validation, and financial impact assessment. The Senior Data Analyst will use SQL and Excel to investigate large datasets, test analytical outputs, evaluate program performance, and turn open-ended business questions into reliable, decision-ready findings. The position works across business, product, analytics, and finance functions. It is primarily focused on analytical problem-solving rather than dashboard development, routine reporting, or requirements documentation.

Responsibilities

• Write complex SQL queries to retrieve, transform, and analyze large datasets in BigQuery or similar cloud data platforms.
• Use SQL and Excel to combine data, perform exploratory analysis, and validate analytical results.
• Investigate trends, unusual patterns, inconsistencies, and potential data-quality concerns.
• Independently test analytical datasets, calculations, methodologies, and assumptions produced by other team members.
• Confirm the accuracy and reliability of analytical conclusions before they are used to support business decisions.
• Estimate the financial and operational effects of proposed programs and business changes.
• Build structured business cases with documented assumptions, analytical methods, and measures of success.
• Connect analytical findings to financial outcomes in collaboration with finance stakeholders.
• Assess program performance and identify practical opportunities for improvement.
• Turn broadly defined business problems into structured analytical questions and plans.
• Determine appropriate data sources and analysis methods based on the problem being evaluated.
• Ask targeted questions to clarify objectives, assumptions, and analytical requirements.
• Adapt analytical methods when available data, systems, or business conditions change.
• Present findings, recommendations, assumptions, and limitations in a clear format for technical and non-technical audiences.
• Collaborate with product managers, data scientists, finance partners, and business stakeholders.

Required experience and skills

• Five or more years of experience in data analysis, business analytics, financial analysis, decision support, or a related discipline.
• Advanced SQL skills with practical experience querying, transforming, and analyzing large datasets.
• Advanced Excel skills.
• Strong experience with data preparation, exploratory data analysis, and data-quality validation.
• Demonstrated ability to convert ambiguous business questions into structured and defensible analytical approaches.
• Experience estimating financial or operational business impact.
• Strong analytical problem-solving skills and intellectual curiosity.
• Ability to independently manage analytical work and adjust to changing priorities.
• Strong written and verbal communication skills.
• Experience with BigQuery or another cloud data platform is preferred.
• Experience collaborating with finance teams or building financial-impact models is preferred.
• Familiarity with Python or another analytical programming language is preferred.
• Experience in healthcare, insurance, pharmacy benefits, or another complex regulated industry is preferred.
• Practical familiarity with how consumers navigate healthcare, insurance, or pharmacy benefits is preferred.

FAQ

1. What does a Senior Data Analyst do?

A Senior Data Analyst analyzes complex datasets to identify trends, answer business questions, and support data-driven decision-making. The role typically combines data extraction, statistical analysis, reporting, visualization, and collaboration with business and technical teams.

2. What types of analysis does a Senior Data Analyst perform?

The role may involve trend analysis, customer or operational analysis, performance reporting, segmentation, forecasting support, and root-cause analysis. Senior analysts are also expected to turn analytical findings into clear recommendations that stakeholders can act on.

3. Which tools are commonly used by Senior Data Analysts?

SQL is commonly used to retrieve, join, transform, and validate data, while Python or R may be used for advanced analysis and automation. Analysts may also work with Power BI, Tableau, Excel, Looker, or other business intelligence and visualization platforms.

4. How does a Senior Data Analyst ensure data accuracy?

Analysts validate source data, investigate inconsistencies, reconcile metrics, and perform quality checks before presenting results. They also document definitions and calculation logic so that reports and analytical outputs remain consistent across teams.

5. What role does SQL play in senior data analysis?

SQL is used to work directly with databases and analytical warehouses, including complex joins, aggregations, subqueries, window functions, and data transformations. Strong SQL skills allow senior analysts to independently investigate large datasets and develop reliable analytical datasets.

6. How does a Senior Data Analyst communicate findings to business stakeholders?

The analyst uses dashboards, visualizations, reports, and concise explanations to translate complex findings into understandable business insights. They focus on the implications of the data and connect analytical results to specific business questions or decisions.

7. Which metrics are important for evaluating analytical work?

The appropriate metrics depend on the business function and analytical objective and may include revenue, conversion, retention, engagement, operational efficiency, customer behavior, or cost-related measures. Senior analysts ensure that metrics are clearly defined and aligned with the decisions they are intended to support.