Data Engineering Architect/Lead
Qualitest
Data Engineering Architect/Lead
Qualitest
AI-powered software testing and quality engineering
Are you interested in working with the World’s leading AI-powered Quality Engineering Company? Ready to advance your career, team up with global thought leaders across industries and make a difference every day? Join us at QualityAI!
We are looking for Data Engineering Architect/Lead to join our growing team in United States
Location - US Remote
Top 3 Must Haves:
1. hands-on experience in data engineering, data architecture or data lake delivery, including 2+ years leading technical teams.
2. Expert in Python, PySpark, SQL, Object oriented programming with production experience on AIDP, Databricks or Snowflake.
3. Uses AI coding tools daily to build production systems and can write the specs and context that make them work well.
Preferred Skills:
Oracle Cloud Infrastructure (OCI), Golden Gate and Autonomous Database.
Data contracts, Data Mesh and governed data marketplace implementation.
Healthcare domains: claims, provider, member, product, finance, acquisition integration.
Platform depth in Terraform, asset bundles, GitHub Actions and Kubernetes.
Experience running distributed onshore and offshore teams.
JD:
Role Summary :
Take the EDL vision and high architecture as defined, turn it into concrete low-level designs, work packages, explain and hand them to the engineering team, and work with the project managers to deliver on phase deadlines. Hands on ~ 50%, deep enough to review, unblock and set the technical bar. Owns outcomes end to end, finds and fixes problems, and multiplies that reach with AI native way of working.
Responsibilities:
-Translate vision into design. Take the architectural direction and produce implementable designs, strategize and translate to tasks. Keep the vision and high-level design intact through delivery without redefining the vision or reducing the scope.
-Build with AI every day using Claude Code, Codex or similar. Write the markdown specs, skills and context files that make coding effective, and review what they produce to a production standard.
-Stay hands on with the Data Lakehouse foundation. Python, PySpark, Delta Lake and medallion design on AIDP (OCI).
-Design data products and semantic structures. Blueprints covering scope, canonical entities, certified metrics, quality rules, lineage, access and publication criteria.
-Set standards for keys, naming conventions, configuration, reference data and metadata, and keep them aligned to the business glossary.
-Understand agentic architecture. How agents consume data and tools, callable services for AI systems, MCP style interfaces, agent traces and observability, and facilitate data access for agents.
-Lead and delegate. Break work down, assign it, review it and coach onshore and offshore engineers. Partner with project managers on planning, estimates and risks.
-Know the platform and governance side. Terraform, asset bundles, CI/CD and environment promotion.
-Turn governance policies such as PHI protection, masking, classification and data quality into controls engineers can actually implement.
-Oracle Golden gate CDC process, creating unified data models on EDL, create pipelines, conformed dimensions and Gold layer delivery to semantic models.
Required Qualifications:
8+ years hands-on experience in data engineering, data architecture or data lake delivery, including 2+ years leading technical teams.
At least 1 year experience building products using AI coding tools like Claude code or Codex.
Knowledge around AI frameworks for Agent observability, MCP server development or knowledge layer design (ontologies, knowledge graphs)
Expert in Python, PySpark, SQL, Object oriented programming with production experience on AIDP, Databricks or Snowflake.
Has designed conceptual, logical, physical and dimensional models and delivered them as governed Gold assets used by BI semantic layers.
Uses AI coding tools daily to build production systems and can write the specs and context that make them work well.
Has built REST services and callable tools consumed by applications or AI agents.
Has delivered under regulated data controls (PHI, HIPAA or equivalent) and against fixed phase deadlines.
Preferred Qualifications or knowledge:
Oracle Cloud Infrastructure (OCI), Golden Gate and Autonomous Database.
Data contracts, Data Mesh and governed data marketplace implementation.
Healthcare domains: claims, provider, member, product, finance, acquisition integration.
Platform depth in Terraform, asset bundles, GitHub Actions and Kubernetes.
Experience running distributed onshore and offshore team
Benefits
Why QualityAI?
Qualitest provides software testing services powered by AI to help clients in healthcare, finance, and technology improve quality and speed up time to market. Its core product is Qualisense, an AI tool that enhances risk-based testing by prioritizing testing efforts, identifying high-risk areas, and optimizing test coverage. This allows Qualitest to automate and accelerate testing workflows, reduce costs, and improve operational efficiency for large, diverse enterprises worldwide. The company differentiates itself from competitors through its focus on AI-driven testing and risk-based strategies, enabling faster release cycles and better customer experiences. Qualitest aims to help organizations deliver reliable software quickly and at lower overall risk by combining specialized testing services with advanced AI-enabled tooling, primarily under long-term service contracts and partnerships.
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