Job description

A leading organization is seeking a Data Analyst to support a document viewing and API enhancement initiative. The position will analyze structured data, develop business intelligence reporting, and provide insights that support access to relevant encounter information. The Data Analyst will work with business and cross-functional stakeholders to translate questions and reporting needs into practical analytical solutions.

Responsibilities

• Analyze large datasets to uncover trends, patterns, and actionable business insights.
• Build and maintain reports, dashboards, and data visualizations using Tableau, Power BI, or similar business intelligence platforms.
• Write and optimize SQL queries to extract, cleanse, and validate information from multiple data sources.
• Gather business requirements and help define key performance indicators.
• Translate business questions into data analysis and reporting solutions.
• Assess data quality and support governance efforts focused on data accuracy and consistency.
• Use Excel, SQL, and analytical tools to support operational reporting and informed decision-making.
• Collaborate with cross-functional teams to deliver data-driven recommendations.

Required experience and skills

• Strong SQL skills for data extraction, validation, and analysis.
• Experience with Tableau.
• Experience with business intelligence and reporting tools.
• Proficiency with Excel for data analysis and operational reporting.
• Ability to analyze large datasets and identify meaningful trends and patterns.
• Experience developing dashboards, reports, and visualizations.
• Ability to gather stakeholder requirements and translate business needs into analytical solutions.
• Understanding of data quality and data governance practices.

FAQs

1. What does a Data Analyst do?

A Data Analyst collects, cleans, analyzes, and interprets data to answer business questions and support decision-making. The role typically involves querying datasets, identifying trends, building reports or dashboards, and communicating findings to stakeholders.

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

Data Analysts may perform trend analysis, performance analysis, segmentation, variance analysis, customer analysis, and root-cause investigations. The specific analysis depends on the business function and the questions stakeholders need answered.

3. How is SQL used in a Data Analyst role?

SQL is commonly used to retrieve, join, filter, aggregate, and transform data from relational databases and data warehouses. Analysts may also use subqueries, common table expressions, and window functions to build datasets for reporting and deeper analysis.

4. Which data visualization tools are commonly used by Data Analysts?

Data Analysts may use platforms such as Power BI, Tableau, Looker, Excel, or similar business intelligence tools to create dashboards and reports. The appropriate tool depends on the organization's data environment, reporting requirements, and stakeholder needs.

5. How does a Data Analyst ensure data quality?

Analysts validate source data, check for missing or duplicate records, investigate inconsistencies, and reconcile results against trusted sources. They also verify metric definitions and calculation logic before using data in reports or business recommendations.

6. How does a Data Analyst turn data into business insights?

The analyst begins with a specific business question, identifies relevant data, performs appropriate analysis, and interprets the results in context. The final output should explain not only what happened in the data but also why it matters and what actions stakeholders may consider.

7. What role does Excel play in data analysis?

Excel can be used for data cleaning, exploratory analysis, calculations, pivot tables, charts, and smaller-scale reporting workflows. Analysts may also use formulas, lookup functions, Power Query, and other Excel capabilities to prepare and analyze datasets.

8. How do Data Analysts work with stakeholders?

Data Analysts collaborate with business, product, finance, marketing, operations, and technology teams to understand requirements and clarify analytical questions. They communicate findings through dashboards, reports, presentations, and concise explanations tailored to the audience.