Job Description

We are seeking a highly skilled Senior Test Automation & Data Engineer to join a high-impact Agile delivery squad working on complex data engineering and quality assurance projects within a large-scale Common Data Platform (CDP) initiative. The ideal candidate will have a strong background in automated testing frameworks, modern data engineering practices, and experience working with cloud technologies, especially AWS. The role involves developing robust test automation strategies and high-quality data pipelines to support regulatory functions with system-wide visibility.

Job Responsibilities:

• Actively participate in Agile ceremonies following Scaled Agile methodologies
• Design, build, and maintain automated test frameworks and reusable test components
• Coordinate and execute data quality assurance across ingestion, transformation, and delivery stages
• Lead the development of end-to-end automated testing strategies
• Design, develop, and maintain data pipelines using Spark, Airflow, and related tools
• Ensure traceability between requirements and test scenarios, tracking progress with quality metrics
• Provide mentorship on testing methods, automation techniques, and quality assurance best practices
• Implement data security and governance best practices
• Collaborate with cross-functional teams including data scientists, analysts, product managers, and stakeholders
• Monitor and troubleshoot data pipelines, implementing alerts and auto-remediation
• Continuously research, evaluate, and recommend modern data tools and frameworks

• Bachelors degree in Computer Science, Information Systems, or a related field
• 7+ years of experience in test automation, data engineering, or software engineering
• 2+ years of experience with modern data stacks (e.g., S3, Spark, Airflow, Lakehouse architectures)
• 2+ years of experience with test automation tools (e.g., Great Expectations, Lambda Test, Selenium, Cucumber)
• Proficiency with SQL and data modeling concepts
• Experience in designing and managing ETL and data pipelines for structured/semi-structured/unstructured data
• Strong understanding of data governance, information security, and architecture principles
• Proficient in AWS services such as S3, EC2, Lambda, Data Pipeline, CloudWatch, etc.
• Excellent analytical, communication, and problem-solving skills
• Ability to work independently and manage multiple tasks in a fast-paced environment

• Experience with Big Data ecosystems
• Familiarity with domain areas such as Supervision and Regulation functions
• Prior experience building data pipelines using Spark on cloud platforms (e.g., AWS)
• Knowledge of CI/CD automation tools and DevOps best practices
• Experience in coaching and mentoring technical teams

AWS certifications or related cloud/data engineering certifications are a plus

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