Role Overview:

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

The role requires strong hands-on expertise in Python, SQL, ETL, Databricks, data modelling, statistical analysis, and healthcare data analytics.

The candidate will work closely with business, clinical, product, data engineering, and technology stakeholders to transform complex healthcare data into meaningful insights.

The role will involve developing analytical datasets, dashboards, reports, data models, and analytical solutions focused on patient outcomes, healthcare quality, operational efficiency, and business performance.

The ideal candidate should have a strong understanding of healthcare data and be comfortable working with large, complex, and sensitive datasets while following appropriate data governance and regulatory requirements.

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.

- Work with stakeholders to understand business and analytical requirements and translate them into data solutions.

- 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.

Healthcare Analytics Responsibilities:

- Analyze healthcare and clinical datasets to support patient and operational insights.

- Work with healthcare metrics such as patient outcomes, quality measures, utilization, readmissions, clinical performance, and operational efficiency.

- Understand relationships between clinical, claims, patient, provider, and operational data.

- Support analytical initiatives related to healthcare quality improvement and performance measurement.

- Identify data quality issues that may impact clinical or operational reporting.

- Ensure analytical outputs are appropriately interpreted within the healthcare business context.

- Work with stakeholders to define healthcare-specific KPIs, metrics, dimensions, and reporting requirements.

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.

- Understanding of data lake, data warehouse, and modern data platform concepts.

- Experience working with structured and semi-structured data.

Data Modelling:

- Strong understanding of analytical and dimensional data modelling.

- Experience designing datasets for reporting and analytics.

- Understanding of fact and dimension tables.

- Experience integrating data from multiple sources.

- Knowledge of data lineage and metadata concepts.

Reporting & Visualization:

- Experience developing analytical dashboards and reports.

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

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

- Experience defining and monitoring business and healthcare KPIs.

Data Governance & Compliance:

- Strong understanding of data quality, data governance, and data management practices.

- Experience working with sensitive or regulated healthcare data.

- Understanding of data privacy, access controls, data security, and regulatory requirements.

- Experience implementing data validation and quality checks.

- Ability to maintain appropriate documentation and governance controls around analytical datasets.

- Exposure to healthcare data standards and regulations would be an advantage.

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.