Job Description
As a Data Analyst – Associate, you will engage with clients to optimize operational efficiency and effectiveness, developing strategies to enhance productivity and drive business performance. Within our Technology Consulting practice, you will focus on providing consulting services to improve operational performance and develop innovative solutions. As an Associate, you will contribute to client engagement and projects while developing your skills and knowledge to deliver quality work. You will be exposed to clients to learn how to build meaningful connections, manage and inspire others, and grow your personal brand by deepening your technical knowledge of firm services and technology resources.
Core Responsibilities at This Level Include:
- Analyzing large healthcare operational datasets to identify trends, performance metrics, and financial
insights. - Designing and developing dashboards and analytics reports using Power BI, Tableau, and Excel.
- Extracting and transforming data using SQL and relational databases.
- Designing and maintaining data pipelines and ETL processes used for analytics and reporting.
- Building and maintaining analytics datasets and data models used for operational dashboards.
- Supporting integration of data from multiple sources including databases, flat files, APIs, and operational
systems. - Leveraging automation tools such as Microsoft PowerApps and Power Automate to streamline data
workflows. - Supporting cloud-based analytics environments including exposure to AWS services.
- Ensuring data accuracy, validation, and monitoring processes across analytics datasets.
- Communicating analytical insights through dashboards, reports, and presentations.
- Adhering to PwC’s Code of Ethics & Business Conduct and ensuring compliance with healthcare data
security standards including HIPAA.
Minimum Degree Required (BQ) *:Bachelor’s Degree
Required Field(s) of Study (BQ):Computer Science, Information Technology, Data Analytics, Data Engineering
Preferred Field(s) of Study: Cloud Computing, Software Engineering
Minimum Year(s) of Experience (BQ) *: US
2+ years of experience
Certification(s) Preferred:
Microsoft Power BI Certification
AWS Certified Cloud Practitioner
Required Knowledge/Skills (BQ):
- Strong experience writing advanced SQL queries including joins, subqueries, window functions,
aggregations, and query optimization. - Experience working with SQL Server or other relational database systems.
- Ability to build and maintain database objects such as tables, views, indexes, and stored procedures.
- Experience extracting and transforming large datasets using SQL-based data processing techniques.
- Strong experience developing operational reports and dashboards using Power BI or Tableau.
- Advanced knowledge of Microsoft Excel, including pivot tables, advanced formulas, and data analysis
techniques. - Experience performing data validation, reconciliation, and troubleshooting data discrepancies.
- Ability to analyze large datasets and identify trends, patterns, and operational insights.
- Strong understanding of data modeling concepts and analytics dataset design.
- Strong analytical thinking and problem-solving skills.
Preferred Knowledge/Skills :
- Experience building or supporting ETL / ELT pipelines.
- Exposure to data integration tools such as Alteryx, Informatica, or similar ETL platforms.
- Exposure to AWS services related to analytics, data storage, or data processing.
- Experience with Microsoft Power Platform (PowerApps, Power Automate) for workflow automation.
- Familiarity with Python or similar scripting languages for data processing or automation.
- Experience working with healthcare datasets or Revenue Cycle Management (RCM) environments.
QUALIFICATIONS: Education / Experience:
- BE/BTECH, ME/MTECH, MBA, BCA/MCA, or a related field, or an equivalent amount of relevant professional experience.
- 2- 4 years of experience in data analytics, data engineering, or reporting roles.
- Hands-on experience working with SQL databases and analytics tools such as Power BI or Tableau.
- Experience building dashboards, analytics datasets, and operational reports.
- Exposure to ETL pipelines or data transformation workflows.
- Experience working with large operational datasets.
- Experience working in healthcare, insurance, or regulated industries is preferred.
