AWS Data Test Automation Lead
3 days ago
Job Title: AWS Data Test Automation Lead
Location: Central London / OR Edinburgh
Daily Rate: £400/day - £450/day
Position Type: Contract Position
Experience Required: Overall: 10 - 12 years | Relevant: 6 - 8 years
Role Overview:
We are seeking an experienced Data Test Automation Technical Lead to join our team, supporting a banking customer based in Central London. This role involves building data testing frameworks from scratch, guiding the team on best practices, and driving data testing excellence within complex data environments.
Key Responsibilities:
- Lead the development and implementation of robust data testing frameworks from the ground up.
- Provide technical guidance and mentorship to the testing team, leveraging hands-on experience with data testing technologies and processes.
- Collaborate with cross-functional teams to ensure data testing aligns with business requirements and data standards.
- Develop scripts and automate data testing processes to ensure data quality and integrity across data lakes and streaming environments.
Essential Skills and Experience:
- Data Testing Expertise: Strong background in data testing, including framework creation and automation.
- API Testing: Proficiency with JMeter for API testing (load and performance testing not required).
- Data Processing with PySpark: Ability to write scripts in PySpark for effective data processing.
- Data Lakes and Streaming Technologies: Familiarity with Data Lakes and hands-on experience with Kafka and StreamSets for data stream processing.
- AWS Cloud Experience: Understanding of AWS cloud environment, particularly for data storage, processing, and management.
- Groovy Scripting: Proficient in using Groovy for automation and scripting.
Qualifications and Attributes:
- 10 - 12 years of overall experience in data and testing roles, with 6 - 8 years of focused experience in data test automation and framework development.
- Demonstrated experience leading testing initiatives, with the ability to guide team members effectively.
- Strong analytical and problem-solving skills, with a keen attention to data accuracy and quality.
- Excellent communication skills to engage effectively with stakeholders and cross-functional teams.
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