Senior Test Engineer

Identifies and raises awareness of risks arising from automation test results. Identifies new and implements existing test frameworks to improve confidence in testing. Proficient in coding languages such as Python, Java, SQL, and scripting languages e.g., Bash. Mentors and advises other team members in testing practices. Automates data and application testing tasks and builds test coverage through existing or new infrastructure. Analyses and reports on test activities, results, issues and risks. Production data analysis to identify root cause of production environment issues. Using Apache Airflow for task orchestration and reviewing output logs. Basic understanding of EMR and reviewing output logs. Basic understanding of data processing using Apache Spark. Use of Jupyter notebooks to query and validate data. Use of Amazon Athena to query and validate data. Use of GitLab for source code management. Use of GitLab pipelines for CI/CD. Analyzing data in multiple formats to ascertain validity of new functionality. Use of AWS console and services such as CloudWatch, IAM, S3, Glue, ECR, EC2, EMR, DynamoDB. Understanding of both server-side and client-side encryption. Basic understanding of dimensional data models and slowly changing dimensions/historic data capture. Basic Python, SQL and familiarity with PySpark.

IaC using Terraform. Understanding of Docker and Dockerization of solutions. Data creation/generation for testing. Experience of understanding how customer expectations transition to applied functionality. Experience with Big Data solution or Data Lakes containing structure and unstructured data.