Data Architect

The Data Architect will support the client’s Enterprise Data and Analytics Platform (EDAP) initiative. This role is responsible for architecting, designing, and engineering a modern cloud-based data and analytics ecosystem, while collaborating closely with Department stakeholders, system integrators, and security teams to ensure alignment with business, governance, and regulatory requirements.

Job Duties:

• Provide architectural leadership and hands-on engineering support for the Enterprise Data and Analytics Platform (EDAP).
• Collaborate with business, technical, and executive stakeholders to translate business needs into scalable data and analytics solutions.
• Design, document, and implement cloud-based data lake, data warehouse, and Lakehouse architectures in AWS and Snowflake.
• Develop current-state and future-state conceptual, logical, and physical data models, including reverse engineering existing systems.
• Design and optimize data pipelines supporting batch, CDC, and streaming integrations using industry-standard tools.
• Implement data quality rules, standards, profiling, lineage, and observability across the data ecosystem.
• Architect and enforce data governance, metadata management, cataloging, and master data management (MDM) solutions.
• Design secure data access using RBAC, ABAC, PBAC, row-level, and column-level security controls.
• Ensure compliance with HIPAA and other regulatory requirements through encryption, masking, anonymization, and privacy controls.
• Support analytics, business intelligence, and data science platforms, including BI, ML, and AI capabilities.
• Collaborate with infrastructure and security teams to design secure, cost-optimized AWS cloud environments.
• Support DevOps/DataOps processes, including CI/CD, testing, monitoring, and performance optimization.
• Review and validate system integrator deliverables, architecture artifacts, and test plans.
• Participate in project meetings, documentation, status reporting, and stakeholder communications.

Required Qualifications:

• Current data and/or analytics certification (e.g., CDMP) OR 18+ hours of relevant data and analytics training/webinars within the last three years.
• 5+ years of experience interfacing directly with business stakeholders and explaining technical architectures and data models to non-technical audiences.
• 6+ years of experience architecting, engineering, implementing, and supporting enterprise data warehouses, including 2+ years using Snowflake.
• 3+ years of experience architecting and supporting cloud-based data lakes using AWS S3 and Apache-based technologies (e.g., Parquet).
• 2+ years of experience designing and implementing cloud-based data Lakehouse platforms such as Databricks, Snowflake, Delta Lake, Hudi, or Iceberg.
• 10+ years of experience in data modeling (conceptual, logical, physical, ER models) and data profiling/reverse engineering; proficiency with Erwin preferred.
• 6+ years of experience designing and engineering data pipelines using ETL, CDC, and streaming approaches with tools such as Informatica, AWS Glue, Spark, Kafka, Kinesis, or MuleSoft.
• 6+ years of experience with SQL programming; 3+ years with Python or similar object-oriented languages; 1+ year developing AWS Lambda functions.
• 5+ years of experience architecting and engineering relational and NoSQL databases (document, graph, key-value, columnar, vector).
• 3+ years of experience designing and implementing AWS cloud infrastructure for enterprise data and analytics platforms.
• 3+ years of experience architecting data security and privacy solutions, including DLP, encryption, masking, RBAC/ABAC, and HIPAA compliance.
• 3+ years of experience designing internal and external data sharing hubs and API-based data exchange solutions.
• 2+ years of experience using DevOps or DataOps practices.
• 5+ years of experience in data and analytics testing, quality assurance, and acceptance processes.
• 3+ years of experience implementing data governance and management tools such as data quality, metadata/catalog, and lineage solutions (e.g., Collibra, Informatica, Precisely).
• 2+ years of experience implementing Master Data Management (MDM) solutions using tools such as Informatica MDM, Semarchy, or Reltio.
• 4+ years of experience implementing analytics and business intelligence platforms such as Power BI, Tableau, or Qlik.
• 2+ years of experience implementing cloud-based data science and machine learning platforms such as AWS SageMaker, SAS Viya, or Dataiku.

Preferred Qualifications:

• Experience working in healthcare, public health, or government environments.
• Experience supporting large-scale data modernization or enterprise analytics programs.
• Experience incorporating AI-assisted data engineering, monitoring, or governance capabilities.
• Strong documentation, presentation, and stakeholder communication skills.
• Experience in healthcare or public-sector data environments.
• Experience with Databricks, Delta Lake, Hudi, or Iceberg.
• Experience implementing AI/ML platforms such as AWS SageMaker or Dataiku.
• Knowledge of DevOps or DataOps practices.

Education:

• Bachelor’s degree in computer science, Data Science, Information Systems, Public Health Informatics, or related field.