KamisPro
We are hiring a hybrid QA Lead for a long-term contract (12 months+). Candidates must be able to go onsite in Adelphi, MD.
Are you ready to lead the charge in quality for a cutting-edge Data & AI platform? You’ll own QA and UAT for a platform built on Databricks, delivering AI/ML solutions, BI dashboards, and high-volume data integrations. You’ll work with tools like Azure Purview, Profisee, and Monte Carlo to ensure our data products meet the highest quality standards.
What you’ll do
Build and lead a QA function: define roles, processes, templates and best practices for data, BI, and automation testing.
Develop, manage and execute test plans for:
ETL/ELT pipelines on Databricks and other platforms
APIs and real‑time data integrations (internal & external)
Perform data validations and quality checks using SQL, Python and tools like Monte Carlo and Great Expectations.
Own functional, integration, regression and smoke testing, track defects, collaborate with development teams.
Lead User Acceptance Testing (UAT): prepare business‑aligned test scenarios, facilitate business users, manage feedback and retest cycles until production readiness.
Drive data governance quality: leverage Azure Purview for cataloging/lineage/compliance; support Profisee for master data consistency; use observability tools for anomaly detection and data reliability.
Operate within a SAFe Agile environment: attend PI planning, sprints, coordinate with DevOps, Data Engineers, Data Scientists and Product Owners; integrate QA into CI/CD pipelines; manage test environments and data provisioning.
Enhance QA automation: build and maintain suites for APIs, data pipelines and quality validation; use test management/defect tools such as Azure DevOps, JIRA and TestRail; continuously improve QA tooling and processes.
What you bring
5 + years in QA roles focused on data platforms and analytics—with direct experience building/leading a QA team in that domain.
Demonstrated expertise testing data pipelines, BI tools, and AI/ML workflows on Databricks.
Strong SQL and Python skills for automation and data validation.
Experience managing UAT with business stakeholders.
API testing and data integration validation experience (Postman, REST Assured).
Comfortable working in a SAFe Agile environment.
Excellent communication skills—able to bridge technical and non‑technical stakeholders.
Nice‑to‑haves
Experience with cloud‑native data platforms (Databricks strongly preferred; Azure Synapse, Snowflake or GCP BigQuery a plus).
Knowledge of MLOps and ML/AI model testing techniques.
Familiarity with data governance and compliance frameworks (GDPR, HIPAA).
ISTQB or similar QA certification.
High‑impact role: you’ll lead QA for advanced AI & data solutions on a modern, Databricks‑powered platform.
Cutting‑edge technologies: work with Monte Carlo, Azure Purview, Profisee and more.
Dynamic, collaborative environment: join a high‑performing cross‑functional team of engineers, data scientists and business users in a SAFe Agile setting.
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Are you ready to lead the charge in quality for a cutting-edge Data & AI platform? You’ll own QA and UAT for a platform built on Databricks, delivering AI/ML solutions, BI dashboards, and high-volume data integrations. You’ll work with tools like Azure Purview, Profisee, and Monte Carlo to ensure our data products meet the highest quality standards.
What you’ll do
Build and lead a QA function: define roles, processes, templates and best practices for data, BI, and automation testing.
Develop, manage and execute test plans for:
ETL/ELT pipelines on Databricks and other platforms
APIs and real‑time data integrations (internal & external)
Perform data validations and quality checks using SQL, Python and tools like Monte Carlo and Great Expectations.
Own functional, integration, regression and smoke testing, track defects, collaborate with development teams.
Lead User Acceptance Testing (UAT): prepare business‑aligned test scenarios, facilitate business users, manage feedback and retest cycles until production readiness.
Drive data governance quality: leverage Azure Purview for cataloging/lineage/compliance; support Profisee for master data consistency; use observability tools for anomaly detection and data reliability.
Operate within a SAFe Agile environment: attend PI planning, sprints, coordinate with DevOps, Data Engineers, Data Scientists and Product Owners; integrate QA into CI/CD pipelines; manage test environments and data provisioning.
Enhance QA automation: build and maintain suites for APIs, data pipelines and quality validation; use test management/defect tools such as Azure DevOps, JIRA and TestRail; continuously improve QA tooling and processes.
What you bring
5 + years in QA roles focused on data platforms and analytics—with direct experience building/leading a QA team in that domain.
Demonstrated expertise testing data pipelines, BI tools, and AI/ML workflows on Databricks.
Strong SQL and Python skills for automation and data validation.
Experience managing UAT with business stakeholders.
API testing and data integration validation experience (Postman, REST Assured).
Comfortable working in a SAFe Agile environment.
Excellent communication skills—able to bridge technical and non‑technical stakeholders.
Nice‑to‑haves
Experience with cloud‑native data platforms (Databricks strongly preferred; Azure Synapse, Snowflake or GCP BigQuery a plus).
Knowledge of MLOps and ML/AI model testing techniques.
Familiarity with data governance and compliance frameworks (GDPR, HIPAA).
ISTQB or similar QA certification.
High‑impact role: you’ll lead QA for advanced AI & data solutions on a modern, Databricks‑powered platform.
Cutting‑edge technologies: work with Monte Carlo, Azure Purview, Profisee and more.
Dynamic, collaborative environment: join a high‑performing cross‑functional team of engineers, data scientists and business users in a SAFe Agile setting.
#J-18808-Ljbffr