Data Architect (Advanced)

SGS Technologie; Tallahassee (FL); On-site; USD 110,000 - 150,000; Full time

Job summary

A data management firm in Tallahassee, Florida is seeking a highly experienced Data Architect (Advanced) to lead enterprise-level architecture for a large-scale Data & Analytics Platform. This position requires deep expertise in data warehousing, cloud platforms, and data governance. The ideal candidate will collaborate across data initiatives to ensure effective architecture design and compliance. The role demands extensive experience with technologies like AWS, SQL, and various data modeling tools.

Qualifications

• 5+ years working directly with business stakeholders.
• 6+ years architecting and supporting enterprise data warehouses.
• 3+ years architecting cloud-based data lakes.

Responsibilities

• Serve as Data Architecture SME for enterprise data and analytics initiatives.
• Lead collaborative sessions to design current and future-state ERDs.
• Define and document enterprise data architecture, standards, and patterns.

Skills

Data warehousing

Data lakes/lakehouse architectures

Cloud platforms (AWS)

Data governance

Analytics

Security

Advanced SQL

Python

Education

Bachelor’s degree in Computer Science or related field

Current Data/Analytics certification

Tools

erwin Data Modeler

Informatica

AWS Glue

MuleSoft

Spark

Tableau

Power BI

Job description

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