Role Overview :

We are looking for an experienced Healthcare Data Analyst to design and deliver data-driven analytics solutions for healthcare and clinical datasets.

Key Responsibilities :

- Design, develop, and maintain scalable healthcare data analytics solutions using Python, SQL, ETL tools, and statistical techniques.

- Analyze clinical, patient, claims, operational, and healthcare performance datasets to identify trends, patterns, and actionable insights.

- Develop analytical data models and datasets to support reporting, dashboards, business analysis, and decision-making.

- Build and optimize data processing workflows using Databricks and related data technologies.

- Develop dashboards, reports, and analytical outputs covering areas such as patient outcomes, quality metrics, operational performance, utilization, and healthcare KPIs.

- Perform exploratory data analysis to identify anomalies, trends, correlations, and opportunities for improvement.

- Apply statistical analysis and modelling techniques to support healthcare-related business problems.

- Develop data transformation and ETL processes to integrate data from multiple healthcare and enterprise sources.

- Write complex and optimized SQL queries for data extraction, transformation, validation, and analysis.

- Work with data engineers to ensure data pipelines provide accurate, reliable, and analysis-ready datasets.

- Validate data quality, completeness, consistency, and accuracy across healthcare datasets.

- Investigate data discrepancies and work with technical teams to identify and resolve root causes.

- Collaborate with clinical, business, product, technology, and data teams to develop customized analytics and reporting solutions.

- Translate complex analytical findings into clear insights and recommendations for business and healthcare stakeholders.

- Support development and monitoring of key healthcare performance indicators and analytical metrics.

- Ensure appropriate data governance, privacy, security, and regulatory compliance practices are followed.

- Maintain documentation related to data sources, transformations, analytical methodologies, metrics, and reporting logic.

- Contribute to continuous improvement of healthcare analytics processes, data models, and reporting frameworks.

Technical Skills :

Programming & Analytics :

- Strong proficiency in Python for data analysis and processing.

- Strong SQL skills, including complex queries, joins, CTEs, window functions, aggregations, and query optimization.

- Experience with Python libraries such as Pandas, NumPy, and SciPy.

- Understanding of statistical concepts and analytical techniques.

- Experience with exploratory data analysis and data visualization.

Databricks & Data Engineering :

- Hands-on experience with Databricks for data processing and analytics.

- Experience working with notebooks, data transformation, and large-scale datasets.

- Understanding of Apache Spark / PySpark would be an advantage.

- Experience developing or consuming ETL/ELT pipelines.

Data Modelling :

- Strong understanding of analytical and dimensional data modelling.

- Experience designing datasets for reporting and analytics.

- Knowledge of data lineage and metadata concepts.

Reporting & Visualization :

- Exposure to tools such as Power BI, Tableau, or equivalent BI platforms.

- Ability to convert complex healthcare data into clear and actionable visual insights.

Required Experience :

- 5 - 10 years of experience in Data Analytics, Healthcare Analytics, Business Intelligence, Clinical Analytics, or a related field.

- Strong hands-on experience with Python and SQL.

- Experience working with Databricks and large-scale datasets.

- Strong understanding of ETL/ELT processes and data modelling.

- Experience developing dashboards, reports, and analytical solutions.

- Experience working with cross-functional business and technical stakeholders.

- Strong analytical and problem-solving skills.

- Ability to communicate complex data insights effectively to technical and non-technical audiences.

Preferred Experience :

- Prior experience in healthcare, life sciences, health insurance, clinical analytics, or healthcare technology.

- Experience working with patient, clinical, claims, provider, or healthcare operational data.

- Exposure to healthcare data standards such as FHIR, HL7, ICD, CPT, or SNOMED would be an advantage.

- Experience with cloud data platforms such as Azure, AWS, or GCP.

- Exposure to machine learning or predictive analytics in healthcare would be an advantage.

- Experience with Spark/PySpark and distributed data processing.

- Knowledge of healthcare data privacy and regulatory frameworks.