Data Analyst – Healthcare (Azure Databricks)

Fractal Analytics•New York, NY

6d•$140,000 - $160,000

About The Position

We are seeking an experienced Senior Data Analyst to drive data analysis, source-to-target mapping, and business-driven data insights across complex healthcare datasets, with a strong focus on claims data. This role will partner closely with business stakeholders, data engineering teams, and analytics initiatives to ensure high-quality, well-governed, and analysis-ready data to support forecasting, reporting, and AI/ML use cases. The ideal candidate will combine strong SQL and data analysis expertise, deep healthcare domain knowledge (claims, provider, member data), and hands-on experience with Azure Databricks and modern data platforms.

Requirements

Strong experience in SQL (advanced querying, optimization)
Hands-on experience with Azure Databricks (Spark, Delta Lake)
Experience with cloud data platforms (Azure, Snowflake, BigQuery is a plus)
Knowledge of data modeling, ETL/ELT concepts, and data warehousing
Strong experience in healthcare data, especially claims data processing
Understanding of provider, member, financial datasets
Familiarity with healthcare data standards and business rules
Expertise in data profiling, root cause analysis, and validation
Experience creating Source-to-Target Mapping documents
Ability to work with ambiguous requirements and drive clarity
Strong problem-solving and troubleshooting skills
Excellent communication and stakeholder management
Ability to work cross-functionally with business and technical teams
Strong ownership and accountability mindset
B.Tech/MCA (Minimum 16 years of formal education)
Overall 8+ years of experience.
Minimum of 3 years of experience in Azure (ADF), Databricks
5 years of experience in writing advanced level SQL.

Nice To Haves

Experience working with Snowflake and cloud-based data warehouses is a plus.

Responsibilities

Perform initial data analysis and profiling of complex healthcare datasets (claims, providers, members, finance).
Create and maintain Source-to-Target Mapping (STM) documents, ensuring traceability and accuracy across systems.
Define and standardize data definitions, business glossary, transformations, and business rules.
Identify data anomalies, trends, and inconsistencies and work towards resolution.
Collaborate closely with business stakeholders to understand requirements and translate them into analytical solutions.
Define and manage data intake processes, onboarding new datasets efficiently.
Act as a bridge between business, SME, data engineering and data science teams for requirement clarification and validation.
Write and validate complex, optimized SQL queries for data extraction, transformation, and validation.
Work with large datasets using Azure Databricks (Spark, SQL, Python/Scala).
Support and validate data pipeline outputs developed in Databricks.
Analyze and handle healthcare claims data, ensuring compliance with domain-specific business rules.
Work with datasets across Claims, Provider, Member, Vision, Dental, and Finance domains.
Ensure correct interpretation of healthcare data structures and coding standards.
Ensure high standards of data quality, consistency, and governance.
Develop and enforce validation frameworks and reconciliation processes.
Document data lineage, definitions, and transformation logic.