BerryDunn’s Healthcare Analytics Practice Group is looking for a Senior Healthcare Data Engineer to join and grow with our practice. Our Data Management and Strategy Practice provides end-to-end data management services to clients across public and private sectors. This position is an attractive opportunity if you’re looking to pivot into the consulting space and have a strong interest in developing a wide range of skills and expertise in healthcare data management and analytics. You can expect a range of projects including, but not limited to:

• Enterprise data management advisory
• Data quality and system analysis
• Business requirements solicitation and analysis
• Designing and building data pipelines, warehouses, data integration, and business intelligence solutions.

• Contribute to all aspects of the Systems Development Lifecycle: Engage in planning, analysis, design, and development of data management, data integration, data warehouse, and business intelligence solutions.
• Participate in Goal Setting: Engage in discussions with the team, clients, and project sponsors to determine project goals and set priorities.
• Translate Requirements: Convert business and technical requirements into detailed data analysis and system design specifications.
• Implement and Maintain Data and Analytic Solutions: Utilize database, programming, and ETL tools to implement and maintain data management and warehousing solutions, creating valuable data analytics assets for clients.
• Collaborate with Interested Parties: Work closely with clients and the BerryDunn team to analyze systems, gather requirements, map data pipelines, and assess data quality.
• Ensure Data Quality: Conduct data quality analysis, investigate and resolve issues to ensure data integrity and accuracy.
• Develop Reports and Analytics: Create and deliver reports and analytic applications using suitable business intelligence or custom tools to meet client needs.
• Optimize Processes: Improve efficiency and reliability of client and BerryDunn data processes through innovative solutions and best practices.
• Leverage AI: Use Artificial Intelligence tools to enhance productivity and improve project deliverables.
• Support Cross-Functional Teams: Collaborate with other groups within BerryDunn to provide support for data and system analysis, data pipeline engineering, and data architecture.
• Mentor and Lead: Provide guidance and mentorship to junior team members, fostering a culture of continuous learning and improvement.
• Stay Current with Industry Trends: Keep abreast of the latest trends and technologies in data engineering, healthcare analytics, and data science to ensure BerryDunn remains at the forefront of the industry.
• Ensure Compliance and Security: Ensure all data solutions comply with industry standards, regulations, and security protocols, particularly those specific to healthcare.

• Extensive Data Engineering Experience: A minimum of five years of experience in data engineering, database development, or data warehouse ETL development.
• Business and System Analysis: A minimum of five years of experience in gathering, analyzing, and defining business and system requirements.
• Programming Proficiency: Intermediate to advanced SQL and Python skills, with a proven ability to write complex queries and optimize database performance. Experience with SAS and other technologies is a plus.
• Cloud Technologies: Experience with Amazon Web Services (AWS), Azure, and Snowflake.
• Data Visualization: Proficiency in data visualization tools such as Tableau, Power BI, or similar, with the ability to create insightful and actionable visual reports.
• API Integration: Experience in developing and consuming APIs for data integration and ensuring seamless data flow between systems.
• Agile Methodologies: Experience working in Agile/Scrum environments, with the ability to adapt to fast-paced, iterative development processes.
• Security Best Practices: Knowledge of data security best practices, including encryption, access controls, and compliance with data privacy regulations (e.g., HIPAA).
• Data Quality Expertise: Strong ability to analyze data with a focus on identifying and resolving data quality issues, ensuring data integrity and accuracy.
• Analytical and Problem-Solving Skills: Demonstrated interest in developing a wide range of data analytics skills to be applied across multiple, diverse projects in a dynamic and changing environment.
• Team Orientation: A team-oriented mindset with a friendly and professional demeanor, coupled with the ability to remain flexible amid changing needs and priorities.
• Collaboration Skills: Ability to work effectively with coworkers and diverse clients through periods of both intense interaction and self-directed work.
• Communication Skills: Excellent written and verbal communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
• Project Management Abilities: Experience in managing projects or leading teams, with strong organizational skills and attention to detail.
• Healthcare Knowledge: Prior experience or familiarity with healthcare data standards, regulations, and practices is a plus.
• Educational Background: A bachelor's degree in computer science, mathematics, statistics, economics, engineering, or another discipline with substantial quantitative coursework. Advanced degrees or relevant certifications are a plus.

• Healthcare claims data experience.
• Experience working for or directly with a Medicaid agency.
• Basic understanding of machine learning concepts and experience with implementing machine learning models.
• Ability to support work in multiple time zones, as needed.