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. #J-18808-Ljbffr