Job Description
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:
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.
Responsibilities:
List of Key Responsibilities for the Position:
Required Qualifications:
Education:
Professional Experience:
Certifications (Preferred but not mandatory):
Technical Skills:
Healthcare Expertise:
Leadership & Communication:
Project Management Skills:
Regulatory Knowledge:
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.
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