Quality Assurance Lead

Quality Assurance Lead

Category:
Testing/Quality Assurance

Main location:
United States, Pennsylvania, Pittsburgh

Position :

J

Employment Type:

Full Time

Position Description:

CGI is looking for a Quality Assurance Lead.
This position is located at our client site five days a week in either Pittsburgh, PA, Dallas, TX, Cleveland, OH, or Birmingham, AL.
We are seeking an experienced Lead Quality Assurance Engineer to lead quality engineering efforts for enterprise scale data platforms and distributed applications. This role is responsible for defining QA strategy, leading test automation initiatives, and ensuring the integrity, reliability, and performance of complex data ecosystems.
The ideal candidate combines deep expertise in big data testing, automation frameworks, database validation, and Dev Ops practices with a passion for building scalable quality engineering solutions. This individual will partner closely with cross functional teams to deliver high quality data and application solutions in a highly regulated enterprise environment.

Your future duties and responsibilities:

. Lead the overall quality assurance strategy, test planning, execution, and reporting across large scale data and application initiatives.
. Design, develop, and maintain automated testing frameworks using Python and PySpark for enterprise data validation.
. Validate large scale data pipelines across Hadoop based technologies, ensuring data accuracy, completeness, consistency, and reliability.
. Develop comprehensive end to end test scenarios covering data ingestion, transformation, batch processing, and downstream integrations.
. Perform database validation, reconciliation, and data quality testing using Oracle PL/SQL and SQL.
. Validate machine learning data pipelines and model workflows, including experiment tracking and data integrity validation.
. Monitor and validate enterprise workflow scheduling processes utilizing enterprise job schedulers.
. Integrate automated testing into CI/CD pipelines using Jenkins, Git, and modern Dev Ops practices.
. Develop Unix/Linux scripts to support automation, batch validation, and operational testing.
. Lead defect management activities including root cause analysis, prioritization, and resolution tracking.
. Ensure testing activities align with enterprise governance, audit, compliance, and data security standards.
. Mentor QA engineers and champion automation, continuous improvement, and quality engineering best practices.

Required qualifications to be successful in this role:

. Bachelor's degree in Computer Science, Information Systems, Engineering, or related discipline (or equivalent experience).
. 8+ years of Quality Assurance or Test Engineering experience, including experience leading QA initiatives.
. Strong programming experience with Python and PySpark.
. Hands on experience testing enterprise Big Data platforms including Hadoop, Hive, Impala, and Sqoop.
. Strong experience validating relational databases using Oracle PL/SQL and SQL.
. Experience working with enterprise workload schedulers such as Control M or similar scheduling platforms.
. Strong Unix/Linux scripting skills.
. Experience implementing QA automation within CI/CD pipelines using Jenkins and Git.
. Understanding of Dev Ops methodologies and automated software delivery pipelines.
. Experience working with container technologies such as Docker and Open Shift.
. Strong analytical, troubleshooting, and problem solving skills, particularly involving complex data environments.
. Excellent communication and collaboration skills with technical and business stakeholders.

Preferred Qualifications

. Experience supporting financial services, banking, or other highly regulated industries.
.

Experience with Financial Crime, AML, Fraud Detection, Risk, or Compliance technology platforms.
.

Experience with cloud native data platforms and services, particularly AWS (Glue, Athena, S3, Sage Maker).
. Experience testing machine learning models, AI workflows, or advanced analytics platforms.
. Knowledge of data governance, metadata management, data lineage, and regulatory reporting.
. Experience leading QA transformation or enterprise automation initiatives.

Technical Environment
Candidates should have experience with many of the following technologies:

. Python
. Py Spark
. Hadoop Ecosystem (HDFS, Hive, Impala, Sqoop)
. Oracle PL/SQL
. SQL
. Jenkins
. Git
. Docker
. Open Shift
. Unix/Linux
. Enterprise Workflow Scheduling Tools
. AWS Data Services (preferred)
. MLflow (preferred)

Other Information:
CGI is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range includes various factors not limited to skill set, level, experience, relevant training, and licensure and certifications. To support the ability to reward for merit based performance, CGI typically does not hire individuals at or near the top of the range for their role.

Compensation decisions are dependent on the facts and circumstances of each…