Automation Engineer​/Data QA​/Tester

Automation Engineer / Data QA/Tester (Mid-level)

Location:

Washington, DC

Job Code: 23-0015

# of Openings: 1

Harper Paige has an upcoming opportunity is for an mid-level Automation Engineer / Data QA/Tester to support a Federal client in the Washington, DC area. The position will be part of a highly collaborative, multi-disciplinary team focused on big data Blockchain solutions for a very diverse user-base.

• Use analytic tools to conduct complex queries
• Performs testing during system development and operations
• Generate test methodologies to integrate within CI/CD operations
• Work with developers to define test cases
• Perform data quality assessments and drive to root causes of any issues identified
• Develops automation solutions to increase data ingestion and normalization system efficiency and reduce potential for errors
• Validates data integrity
• Validates quality and accuracy of data and technical deliverables
• Produces and maintains QA-related SDLC documentation
• Documents and escalates major or recurring quality issues to Technical Lead and System Architect for root cause analysis and resolution
• Serves as backup for Senior Developer/Blockchain Specialist for data deliverable production
• Upon completion of integration activities, create a test plan/test procedure to support system acceptance testing
• Conduct system acceptance testing in accordance with approved test plan and test procedures
• After complete of system acceptance testing, provide a test inspection report
• Provide recommendations/input to final system design documents, as appropriate
• Design, develop, and execute testing scenarios that provide coverage of business functions
• Perform triage and analysis of failures in complex multi-system environments
• Develop automation frameworks performing functional and performance testing of API services
• Work closely with product management, business analyst, and development resources throughout delivery of solutions
• Must be comfortable with ambiguity and willing to follow where the data leads

• Bachelors Degree in Computer Science, Engineering, or a related field
• Must have 6+ years of experience triaging, developing, debugging, executing, and monitoring automated tests for big data
• Intermediate knowledge of Unix/Linux-based systems and command-line tools
• Understanding of principles and applications in data management using SQL, Python, R, etc.
• Experience with AWS cloud, EMR, Glue, Spark, Hadoop
• Knowledge of containerization technologies (Docker, Kubernetes) and microservices architecture
• Experience with continuous integration and continuous deployment (CI/CD) pipelines and tools like Jenkins, Git Lab, CI, or CircleCI
• Experience in understanding requirements to identify the solutions the meet the needs
• Proficiency in building frameworks and automating complex workflows using Python
• Experience with Bash for automation and scripting tasks and SQL/PLSQL languages
• Experience with Framework/Plugins tools like REST Assured, Cucumber, Serenity, Selenium Web Driver, and Gherkin Syntax
• Strong knowledge of RESTful Web Services, JDBC technologies, JSON, HTML, XML, GIT/Subversion
• Performance testing knowledge in major databases MongoDB, Redshift, and Starburst data lakes
• Understanding of system architecture and design
• Knowledge of blockchain and crypto data is a plus
• Excellent written and verbal communication skills
• Strong ability to manage time and organize priorities within deadlines.
• Agile scrum/Kanban experience, having worked on cross-functional teams.
• Ability to obtain a public trust and maintain a Public Trust Security Clearance
• Must be a US Citizen (not dual citizen)

Harper Paige provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, Harper Paige complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.