Data Architect -Eli Lilly

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

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).

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.

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

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).

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.