As a Technical Specialist – Data Engineer, you will be a part of an Agile team to build healthcare applications and implement new features while adhering to the best coding development standards.

Responsibilities: -

Design logical and physical data models using specified tools and methods.
Define entities and source system mappings.
Collaborate with business teams to create source-to-target mappings.
Work on HEDIS measures and Clinical EPIC data to analyze and interpret healthcare performance metrics.
Develop and optimize SQL queries for efficient data extraction, transformation, and analysis.
Design and implement data models to support healthcare analytics, reporting, and downstream applications.
Leverage Databricks for scalable data processing, data pipelines, and analytics workflows.
Apply critical thinking and problem-solving skills to address complex data challenges and derive meaningful insights.
Develop Power BI dashboards and reports for effective healthcare data visualization and decision-making.
Collaborate with clinical analysts, data engineers, and business stakeholders to understand requirements and deliver data-driven solutions.
Ensure data quality, integrity, and compliance with HIPAA, NCQA, and other healthcare regulations and best practices.
Automate data validation and reconciliation processes to improve data consistency and accuracy.
Support performance tuning and optimization of SQL queries and data pipelines for efficient processing.

Educational Qualifications: -

Engineering Degree – BE / BTech / BCS
Technical certification in multiple technologies
Certification in Azure, Databricks, or healthcare analytics-related domains

Skills: -

Mandatory Technical Skills: -

Experience in developing and managing data pipelines in Databricks using PySpark/Spark SQL
Strong data modeling skills to design efficient and scalable healthcare data structures
Power BI for data visualization, dashboard creation, and report generation
Strong understanding of healthcare data standards, including HL7, FHIR, and CCDA
Experience in ETL processes and performance tuning for large datasets
Familiarity with Azure Data Services (ADLS, ADF, Synapse) for Cloud-based data management
Proficiency in data modeling tools such as Erwin
Strong understanding of data management concepts
Knowledge of the provider domain
Familiarity with data integration, and ETL tools and techniques
Excellent problem-solving and analytical skills
Strong communication and collaboration abilities
Knowledge of healthcare and pharmacy data
Extensive experience in data modeling and data profiling, with a strong understanding of data management concepts.
Hands-on experience with data modelling tools such as Erwin is highly desirable.
Must have knowledge in healthcare. A good knowledge of the Provider workflows and Pharmacy data is essential.
Familiarity with data integration and ETL concepts, techniques, and tools.

Good to Have Skills: -

Experience in Python and PySpark for data transformation and analysis
Knowledge of Confluent Kafka or event-driven architecture for real-time data processing
Hands-on experience in NoSQL databases like MongoDB or Snowflake for scalable data storage
Understanding of data governance frameworks and compliance in healthcare analytics
Exposure to CI/CD pipelines and DevOps practices in Cloud environments
Familiarity with Machine Learning concepts for predictive healthcare analytics