DATA ARCHITECT
DIRECT HIRE (USC/GC ONLY)
ATLANTA, GA (HYBRID)
OVERVIEW
Our client is seeking a hands-on Data Architect who will serve as the organizations primary data expert.
- This individual will own the architecture, modeling, performance optimization, and governance of all data systems.
- The company currently has no dedicated data professionals outside of a DBA and is actively hiring an offshore data engineer to support smaller-scale work.
- The Data Architect will set standards, define direction, and architect scalable solutionsparticularly around AWS, Databricks, multi-tenant design, and real-time data streaming.
- Candidates with 24+ years of Databricks experience typically have the core technical foundation needed for this role.
KEY RESPONSIBILITIES
- Architect, design, and optimize enterprise data solutions across AWS environments (structured, unstructured, relational, and NoSQL sources).
- Design logical and physical data models, including ER diagrams, dimensional models, and multi-tenant schemas.
- Lead performance tuning and optimization efforts for Oracle and PostgreSQL databases.
- Define and implement OLTP and OLAP architectures, including data warehousing and ETL/ELT best practices.
- Build and support real-time data streaming solutions (including CDC, queuing technologies like Kafka, and event-driven pipelines).
- Enable near real-time delivery of data changes directly to customers for consumption within their own data lakes.
- Architect and grow modern data lake and environments, ideally leveraging Databricks as the strategic platform.
- Collaborate with engineering teams and offshore resources to deliver scalable, reliable, and well-governed data systems.
- Establish standards, best practices, and architectural patterns for enterprise data management.
- (Preferred) Build or enhance data platforms that support AI/ML workloads, including data readiness, optimization, and pipelines feeding AI models.
REQUIRED EXPERIENCE
- Databricks experience (required) strong working proficiency with 24+ years strongly preferred.
- Deep AWS data ecosystem experience , including design and hands-on engineering with structured, unstructured, relational, and NoSQL data.
- Database expertise in Oracle and PostgreSQL including schema design, indexing, and performance tuning.
- Strong data modeling skills; ability to design optimal models and produce professional ER diagrams.
- Near-expert experience optimizing databases for performance and scalability.
- Strong understanding of multi-tenant architectures , including schema isolation and workload management.
- Experience with both OLTP and OLAP systems, including modern data warehousing and ETL/ELT patterns.
- Experience with CDC, data streaming, and queuing systems (e.g., Kafka, Kinesis, Pulsar).
- Ability to architect data sharing solutions enabling customers to ingest data in their own data lakes.
- Experience designing or supporting data pipelines optimized for AI/ML workloads, including feature engineering, vector storage, model-ready datasets, or integration with AI platforms (e.g., SageMaker, Databricks ML, or similar).
PREFERRED QUALIFICATIONS
- Experience building data lakes that support AI or advanced analytics.
- Experience designing data architectures that feed or support AI/ML models.
- Previous ownership of enterprise data strategy or acting as the primary data expert within an organization.
- Master's Degree
IDEAL CANDIDATE PROFILE
- Hands-on, highly technical Data Architect who can own end-to-end data architecture.
- Comfortable being the go-to data authority in an environment with limited existing data expertise.
- Strategic, forward-thinking, and experienced in shaping modern cloud-native data ecosystems.
- Strong communicator capable of working across teams and guiding offshore resources.