AI Data Architect
At a glance
Mid-level Data Architecture & Governance role at Innovative Solutions. Remote, United States · full-time · $150,000–$200,000 base.
dataroles summary, based on the employer's posting.
What you'll do
- Build S3 data lakes with organized zones, partitioning, retention rules, and encryption
- Create warehouse models and ETL pipelines using Glue, with Redshift, Snowflake, or Databricks
- Shape warehouse data for BI through dimensional schemas, materialized views, and gold-layer models
- Design AI systems including Bedrock-based RAG search, document processing, and SageMaker ML pipelines
- Guide client discovery, present architecture choices, mentor delivery teammates, and assess AWS data and AI tools
What you bring
- At least five years in professional IT, including two years working with AWS
- An AWS Professional-level certification, such as Solutions Architect Professional or Data Engineer Specialty
- Python and PySpark skills for data pipelines, plus SQL and NoSQL schema design and query tuning on AWS
- Hands-on knowledge of AWS data modeling, medallion architecture, Glue ETL, and S3 lake design
Who this fits
This role suits a mid-career data architect who can own varied AWS data and AI projects and advise both technical and business audiences. It is remote, with two weeks of travel to Rochester, New York, each quarter.
From the employer
As a Data/AI Architect, you'll design and build data-driven cloud architectures on AWS — from S3 data lakes and Glue ETL pipelines to data warehouses and RAG-powered AI systems. You'll own the full data stack across a variety of industries and projects: one engagement you're designing a Redshift data warehouse with medallion architecture processing 31M transactions/month, the next you're building a Bedrock Knowledge Base with OpenSearch vector search. Real ownership, real variety.
Location: This can be a remote opportunity, with 2 weeks of travel into Rochester, NY per quarter
What You'll Do:
- Design and build S3 data lakes with multi-zone organization, partitioning strategies, lifecycle policies, and encryption
- Implement medallion architecture (bronze/silver/gold) for data warehouses on Redshift, Snowflake, or Databricks
- Build AWS Glue ETL pipelines (Python Shell and Spark) with incremental extraction, Data Catalog management, and optimized Parquet output
- Design star/snowflake schemas, materialized views, and gold-layer models optimized for BI consumption (QuickSight, PowerBI)
- Configure data warehouse platforms — Redshift with Zero-ETL from Aurora, Snowflake with Snowpipe, Databricks with Delta Lake and Auto Loader
- Design RAG systems using Bedrock Knowledge Base with OpenSearch Serverless vector search and Titan Embeddings
- Architect document AI pipelines using Textract, Comprehend, and Bedrock for entity extraction
- Design SageMaker ML pipelines for training, Model Registry, and inference
- Lead data discovery sessions with client stakeholders and present architecture recommendations to technical and business audiences
- Mentor delivery team members on data architecture patterns and AWS data services
- Contribute to R&D projects evaluating emerging AWS data and AI capabilities
Required Skills:
- 5+ years professional IT experience, 2+ years professional AWS experience
- At least one AWS Professional-level certification (Solutions Architect Professional or Data Engineer Specialty preferred)
- Python for data pipelines (Glue jobs, Lambda, SageMaker scripts) and PySpark for Glue Spark jobs
- SQL and NoSQL on AWS — Aurora PostgreSQL, RDS PostgreSQL, DocumentDB, DynamoDB — including schema design and query optimization
- Data modeling — conceptual, logical, and physical models for AWS data platforms; normalized silver-layer schemas, denormalized star/snowflake gold-layer schemas, data dictionaries
- Dimensional modeling and medallion architecture (bronze/silver/gold) on Redshift, Snowflake, or Databricks, including materialized views and incremental refresh patterns
- AWS Glue ETL (Python Shell and Spark), Glue Data Catalog, and crawlers
- S3 data lake architecture with partitioning, lifecycle policies, and encryptions
Preferred:
- RAG systems with Bedrock Knowledge Base and OpenSearch Serverless vector search
- Amazon SageMaker for ML training, Model Registry, and inference
- AWS HealthLake, FHIR R4 transformation, and HIPAA-compliant data pipelines
- Document AI with Amazon Textract and Comprehend
- Amazon Athena, QuickSight, or PowerBI integration
- Terraform or CloudFormation for data infrastructure as code
- Step Functions, EventBridge, and Lambda for event-driven pipeline orchestration
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Data Architecture & GovernanceRemote$150k+
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