Q

Qualitest

AI-powered software testing and quality engineering

Data Engineering Architect/Lead

Data EngineeringPosted on Nov 12
Full-timeRemote in USA

About the Job

Requirements

  • At least 8 years of hands-on experience in data engineering, data architecture, or data lake delivery, including at least 2 years leading technical teams.
  • At least 1 year of experience building products using AI coding tools such as Claude Code or Codex.
  • Knowledge of AI frameworks for agent observability, Model Context Protocol (MCP) server development, or knowledge-layer design such as ontologies and knowledge graphs.
  • Expertise in Python, PySpark, SQL, and object-oriented programming, with production experience on AIDP, Databricks, or Snowflake.
  • Experience designing conceptual, logical, physical, and dimensional models and delivering them as governed Gold assets used by BI semantic layers.
  • Experience using AI coding tools daily to build production systems and writing effective specifications and context.
  • Experience building REST services and callable tools consumed by applications or AI agents.
  • Experience delivering under regulated data controls such as PHI protection or HIPAA, or equivalent, and against fixed phase deadlines.

Responsibilities

  • Translate architectural direction into implementable designs, strategies, and work tasks while preserving the established vision and scope through delivery.
  • Build with AI coding tools such as Claude Code, Codex, or similar; write markdown specifications, skills, and context files, and review generated work to production standards.
  • Work hands-on with the Data Lakehouse foundation using Python, PySpark, Delta Lake, and medallion design on AIDP (OCI).
  • Design data products and semantic structures, including blueprints for scope, canonical entities, certified metrics, quality rules, lineage, access, and publication criteria.
  • Set standards for keys, naming conventions, configuration, reference data, and metadata, aligned with the business glossary.
  • Apply agentic architecture concepts, including agent data and tool consumption, callable services for AI systems, MCP-style interfaces, agent traces and observability, and data access for agents.
  • Break work into tasks, delegate and review work, and coach onshore and offshore engineers; partner with project managers on planning, estimates, and risks.
  • Apply platform and governance practices using Terraform, asset bundles, CI/CD, and environment promotion.
  • Translate governance policies such as PHI protection, masking, classification, and data quality into implementable engineering controls.
  • Develop Oracle GoldenGate CDC processes, create unified data models on EDL, build pipelines and conformed dimensions, and deliver the Gold layer to semantic models.

Desired Qualifications

  • Knowledge of Oracle Cloud Infrastructure (OCI), GoldenGate, and Autonomous Database.
  • Experience implementing data contracts, Data Mesh, and governed data marketplaces.
  • Knowledge of healthcare domains, including claims, provider, member, product, finance, and acquisition integration.
  • Platform experience with Terraform, asset bundles, GitHub Actions, and Kubernetes.
  • Experience running distributed onshore and offshore teams.

About the Company

Qualitest

AI-powered software testing and quality engineering

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.

Company size
1,001-5,000
Company stage
Acquired
Total funding
$497M
Headquarters
Fairfield, CT
Founded
1997

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