Project Overview: Project Description | Problem Statement: Role Overview:We are seeking a talented Senior Data Architect with expertise in designing, building, and maintaining data architecture for healthcare analytics. The ideal candidate will have a strong background in setting up processes, defining data models, and implementing data governance frameworks. Experience with medical insurance data, including Medicare, Medicaid, and state healthcare programs, is highly preferable. Responsibilities:  Collaborate with stakeholders to understand business requirements and translate them into scalable data architecture solutions.  Design and develop data models, data warehouses, and data lakes to support the storage, integration, and analysis of large volumes of healthcare data.  Define data standards, policies, and procedures to ensure data quality, integrity, and security across the organization.  Implement data governance processes to manage metadata, data lineage, and data access controls.  Evaluate and select appropriate technologies and tools to support data architecture and analytics requirements.  Lead the implementation of data migration, transformation, and ETL processes to enable seamless data integration and interoperability.  Work closely with data engineers, data scientists, and other stakeholders to ensure alignment with business objectives and technical requirements.  Stay current with emerging trends and best practices in data architecture, healthcare analytics, and regulatory requirements in the medical insurance industry.  Provide technical leadership, guidance, and mentorship to junior team members.  Position Title: Senior Data Architect Required Skills: • Data Architecture Expertise: • Proven experience in designing, developing, and maintaining data architectures for large-scale systems. • Strong understanding of data modeling (conceptual, logical, and physical) and database design principles. • Familiarity with relational, NoSQL, and cloud-based databases (e.g., SQL Server, MySQL, MongoDB, AWS, Azure). • Healthcare Analytics Knowledge: • Extensive experience with healthcare data, including Medicare, Medicaid, and state healthcare programs. • Knowledge of healthcare regulatory requirements, HIPAA compliance, and PHI data management. • Experience with medical insurance claims, clinical data, and other healthcare datasets. • Data Governance & Quality Management: • Expertise in implementing data governance frameworks, including metadata management, data lineage, and data stewardship. • Familiarity with data quality management practices to ensure accuracy, completeness, and reliability of data. • ETL & Data Integration: • Experience with ETL processes, data migration, and data transformation. • Hands-on experience with data integration tools (e.g., Informatica, Talend, Apache NiFi) and cloud data services. • Data Warehousing & Data Lakes: • Strong knowledge of data warehousing solutions, data lakes, and data lakehouses for storing and analyzing large volumes of structured and unstructured data. • Familiarity with technologies like Snowflake, Redshift, Databricks, or Google BigQuery. • Cloud Technologies: • Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud for data storage, analytics, and services. • Familiarity with cloud-native data architecture, serverless computing, and infrastructure-as-code. • Data Security & Compliance: • Proficiency in ensuring data security, privacy, and access control for sensitive healthcare data. • Experience with encryption techniques, access control, and compliance with industry standards such as HIPAA. • Technical Leadership & Collaboration: • Strong ability to collaborate with cross-functional teams, including data engineers, data scientists, and business analysts. • Experience leading technical teams, mentoring junior members, and providing architectural guidance. • Ability to communicate effectively with both technical and non-technical stakeholders. • Tools & Technologies: • Proficiency in data modeling tools (e.g., Erwin, PowerDesigner). • Experience with data visualization tools (e.g., Tableau, Power BI) and analytical frameworks (e.g., Spark, Hadoop). • Knowledge of programming languages such as SQL, Python, and Scala. • Regulatory Compliance & Emerging Trends: • In-depth understanding of healthcare regulations and staying current with emerging trends in data architecture, healthcare analytics, and medical insurance. Desired Experience Level: • Data Architecture & Modeling: At least 7-10 years of experience designing and implementing complex data architectures, including data modeling and database design, particularly with large datasets. • Healthcare Analytics & Medical Insurance Data: At least 5 years of experience working with healthcare data, especially in areas like Medicare, Medicaid, and state healthcare programs. This includes familiarity with healthcare regulations, compliance, and privacy requirements. • Data Governance & Quality: 3-5 years of experience setting up and managing data governance frameworks, including defining data standards, policies, and procedures. • Technical Leadership & Mentorship: 3-5 years in a leadership capacity, guiding and mentoring junior team members, and working cross-functionally with other departments like data science and engineering. • Cloud & ETL Experience: Several years (at least 3-5) of hands-on experience with cloud data services (AWS, Azure, etc.) and ETL processes, ensuring data integration and migration strategies. Responsibilities: List of Key Responsibilities for the Position: • Collaborate with stakeholders to understand business requirements and translate them into scalable data architecture solutions. • Design and develop data models, data warehouses, and data lakes to support the storage, integration, and analysis of large volumes of healthcare data. • Define data standards, policies, and procedures to ensure data quality, integrity, and security across the organization. • Implement data governance processes to manage metadata, data lineage, and data access controls. • Evaluate and select appropriate technologies and tools to support data architecture and analytics requirements. • Lead the implementation of data migration, transformation, and ETL processes to enable seamless data integration and interoperability. • Work closely with data engineers, data scientists, and other stakeholders to ensure alignment with business objectives and technical requirements. • Stay current with emerging trends and best practices in data architecture, healthcare analytics, and regulatory requirements in the medical insurance industry. • Provide technical leadership, guidance, and mentorship to junior team members. Required Qualifications: Education: • Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field. • A master’s degree or higher in Data Architecture, Data Science, Healthcare Informatics, or a related field is preferred. Professional Experience: • 10-15 years of experience in data architecture, data modeling, and database design, including experience with large-scale systems in the healthcare domain. • 5+ years of experience working with healthcare data, specifically Medicare, Medicaid, or state healthcare programs. • Strong experience with data governance frameworks and healthcare regulatory standards, including HIPAA compliance. Certifications (Preferred but not mandatory): • Certified Data Management Professional (CDMP). • AWS Certified Solutions Architect, Azure Data Engineer Associate, or similar cloud certifications. • Certified Information Systems Security Professional (CISSP) or other relevant security certifications. • Healthcare-related certifications (e.g., Certified Healthcare Data Analyst (CHDA)) are a plus. Technical Skills: • Proficiency with data modeling tools (e.g., Erwin, PowerDesigner). • Strong programming skills in SQL, Python, or other relevant languages. • Experience with data warehousing solutions (e.g., Snowflake, Redshift, Google BigQuery), ETL tools (e.g., Informatica, Talend), and cloud platforms (AWS, Azure, Google Cloud). • Deep knowledge of relational and NoSQL databases (e.g., MySQL, SQL Server, MongoDB). Healthcare Expertise: • Solid understanding of healthcare data structures, medical insurance systems, and regulatory compliance, including experience with claims data and clinical data sets. • Experience with healthcare analytics and data integration between different systems and providers. Leadership & Communication: • Proven ability to lead teams, provide technical guidance, and mentor junior staff. • Strong collaboration skills with cross-functional teams, including data engineers, scientists, and business stakeholders. • Excellent verbal and written communication skills to explain complex technical concepts to non-technical stakeholders. Project Management Skills: • Experience leading data migration, transformation, and integration projects in a healthcare setting. • Familiarity with Agile or other project management methodologies is a plus. Regulatory Knowledge: • In-depth understanding of healthcare regulations such as HIPAA, and familiarity with ensuring data privacy and security in compliance with industry standards.