Data Architect (Advanced)

We are seeking a highly experienced Data Architect (Advanced) to provide enterprise-level architecture leadership for a large-scale Data & Analytics Platform . The ideal candidate will have deep expertise across data warehousing, data lakes/lakehouse architectures, cloud platforms (AWS), data governance, analytics, and security , with the ability to translate complex technical concepts to business stakeholders.

This role requires strong hands-on technical depth combined with strategic thinking, stakeholder collaboration, and leadership across data initiatives.

Required Qualifications

• Bachelor’s degree (4-year) in Computer Science, Data Science, Analytics, Information Systems, Business Administration, Public Health Informatics , or a related field
• Current Data/Analytics certification (e.g., CDMP)
• OR 18+ hours of data & analytics-related webinars/conferences within the last 3 years

Experience Requirements

• 5+ years working directly with business stakeholders; strong understanding of business operations (healthcare experience preferred)
• 6+ years architecting, engineering, implementing, and supporting enterprise data warehouses , including 2+ years with Snowflake
• 3+ years architecting and supporting cloud-based data lakes (AWS S3, Parquet, layered lake architecture)
• 2+ years architecting lakehouse platforms (Databricks, Snowflake, Delta Lake, Hudi, Iceberg)
• 10+ years of data modeling experience (Conceptual, Logical, Physical, ERD) including schema-on-read and schema-on-write
• Proficiency with erwin Data Modeler required
• 6+ years working with data integration and pipeline tools (ETL, CDC, streaming) such as:
• Informatica, AWS Glue, MuleSoft, Spark, Kafka, Kinesis
• 6+ years of advanced SQL
• 3+ years of Python or similar object-oriented language
• 1+ year of AWS Lambda development
• 5+ years designing and engineering relational (row & columnar) and NoSQL databases (Document, Graph, Key-Value, Vector)
• 3+ years designing AWS cloud infrastructure in collaboration with infrastructure and security teams
• 3+ years implementing data security, privacy, and access controls (RBAC/ABAC, HIPAA-focused compliance)
• 3+ years designing and implementing data sharing hubs and APIs
• 2+ years experience with DevOps/DataOps practices
• 5+ years of data testing, QA, and validation , including automation
• 3+ years implementing data governance tools :
• 2+ years implementing Master Data Management (MDM) solutions
• 4+ years implementing Analytics & BI platforms (Power BI, Tableau, Qlik)
• 2+ years implementing Data Science & Machine Learning platforms (SageMaker, SAS Viya, Dataiku)

Key Responsibilities

• Serve as Data Architecture SME for enterprise data and analytics initiatives
• Analyze and reverse-engineer source systems to understand current-state data models, flows, and quality issues
• Lead collaborative sessions to design current and future-state ERDs and data models
• Define and document enterprise data architecture , standards, and integration patterns
• Develop and enforce data quality rules (accuracy, completeness, timeliness, consistency, validity, uniqueness)
• Support development of data strategy and roadmap aligned with business goals
• Provide architectural guidance across:
• Data warehouse
• Data lake & lakehouse
• Data integration
• Data governance & MDM
• Security & compliance
• Review and validate testing strategies and QA plans for data solutions
• Collaborate with technical and business teams to ensure scalable, secure, and compliant data solutions