Description

What You'll Do: 

• Perform detailed data analysis, profiling, and assessment of complex healthcare datasets.
• Create and maintain Source-to-Target Mapping (STM) documents to ensure data traceability, consistency, and accuracy.
• Define business rules, transformation logic, data definitions, and business glossaries.
• Analyze data anomalies, trends, inconsistencies, and quality issues and drive resolution activities.
• Collaborate with business stakeholders to understand requirements and translate them into analytical solutions.
• Manage data onboarding and intake processes for new business datasets.
• Act as a liaison between business users, SMEs, Data Engineering teams, and Data Science teams.
• Develop and validate advanced SQL queries for data extraction, transformation, reconciliation, and validation.
• Work with large datasets using Azure Databricks, Spark, SQL, Python, and cloud-based analytics platforms.
• Validate and support data pipeline outputs generated by engineering teams.
• Ensure high standards of data quality, governance, consistency, and compliance.
• Design and implement validation frameworks, reconciliations, and data quality controls.
• Document data lineage, business rules, metadata, and transformation logic.
• Support reporting, forecasting, operational analytics, business intelligence, and AI/ML initiatives.
• Partner with engineering teams to build scalable, secure, and reliable data solutions.

Expertise You'll Bring:

• 6-10 years of experience in Data Analysis, Healthcare Analytics, Data Engineering, or Business Intelligence environments.
• Strong experience working with healthcare datasets, especially Claims, Provider, Member, Vision, Dental, and Financial data.
• Advanced SQL expertise including query optimization, performance tuning, profiling, validation, and reconciliation activities.
• Hands-on experience with Azure Databricks, Spark, Delta Lake, and cloud-based data platforms.
• Strong proficiency in Python for data analysis, automation, validation, and reporting.
• Experience creating Source-to-Target Mapping (STM) documents and business mapping artifacts.
• Strong understanding of data warehousing, dimensional modeling, ETL/ELT processes, and enterprise analytics platforms.
• Experience working with Azure cloud services and modern data ecosystems.
• Exposure to Snowflake, BigQuery, or other cloud-based data warehouses is preferred.
• Expertise in root cause analysis, data quality assessment, and issue resolution.
• Experience supporting Business Intelligence, Advanced Analytics, Reporting, and AI/ML initiatives.
• Ability to work effectively with ambiguous requirements and drive clarity through structured analysis.
• Strong analytical, troubleshooting, and problem-solving capabilities.
• Excellent communication, stakeholder management, and collaboration skills.
• Strong ownership mindset and ability to independently manage critical analytical initiatives

Key Skills

Education

Any Graduate