Data Warehousing Analyst (Healthcare)

CIYIS is seeking an experienced Data Warehouse Analyst to support healthcare analytics, business intelligence, reporting, and data-driven decision making initiatives. The successful candidate will work with large, complex healthcare datasets to develop insights, identify trends and anomalies, support program integrity initiatives, and deliver actionable business intelligence solutions., + Analyze large healthcare datasets including claims, provider, encounter, eligibility, and operational data.

• Identify trends, anomalies, risks, and opportunities through advanced analytical techniques.
• Design, develop, and maintain dashboards, reports, and business intelligence solutions.
• Develop and optimize SQL queries, datasets, data models, and reporting solutions.
• Collaborate with business stakeholders to gather requirements and translate analytical needs into technical solutions.
• Develop and validate data extracts that support operational reporting, regulatory reporting, and performance measurement activities.
• Create technical documentation, data dictionaries, reporting methodologies, and process documentation.
• Support data quality initiatives and ensure accuracy and integrity of data assets.
• Present analytical findings and recommendations to business leaders and stakeholders.
• Participate in special projects involving predictive analytics, machine learning, fraud detection, and performance improvement initiatives.
• Support data governance, security, privacy, and compliance requirements.
• Perform other duties as assigned.

This role requires strong analytical and technical skills with the ability to communicate findings effectively to technical and non-technical stakeholders. The ideal candidate has experience working with healthcare claims, provider, eligibility, or encounter data and is comfortable operating in highly regulated environments involving Protected Health Information (PHI)., + Bachelor’s degree in Data Science, Statistics, Computer Science, Information Systems, Mathematics, Analytics, or a related field.

• Minimum of 5 years of experience in data analytics, business intelligence, data warehousing, or reporting.
• Strong SQL experience, including complex query development and performance optimization.
• Experience using SAS, Python, or comparable analytical tools.
• Experience developing dashboards and reports using Tableau, Power BI, SSRS, or similar visualization platforms.
• Strong understanding of data warehousing concepts and analytical methodologies.
• Exceptional analytical, problem-solving, and critical thinking skills.
• Excellent verbal and written communication skills.
• Ability to communicate complex technical information to non-technical audiences.
• Ability to work independently and collaboratively in team environments., + Healthcare, Medicaid, Medicare, payer, or health services analytics experience.
• Experience with healthcare claims, provider, eligibility, encounter, or population health data.
• Experience supporting fraud, waste, abuse, compliance, or program integrity initiatives.
• Experience working with government healthcare programs or public sector organizations.
• Experience with cloud platforms such as Microsoft Azure or AWS.
• Experience with machine learning, predictive analytics, statistical modeling, or risk stratification methodologies.
• Knowledge of HIPAA, healthcare data governance, and regulatory reporting requirements.
• Experience with data extraction, transformation, and loading (ETL) processes.

Desired Technical Skills

• SQL Server
• SQL
• SAS
• Python
• Tableau
• Power BI
• SSRS
• Azure
• AWS
• ETL Development
• Data Warehousing
• Data Modeling

CIYIS is a management consulting, technology, and engineering services firm that helps government, healthcare, and critical infrastructure organizations modernize operations, improve decision-making, and leverage data-driven solutions. We combine deep business expertise with advanced analytics, digital transformation, and technology modernization capabilities to solve complex organizational challenges.