Data Engineer

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: 

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: