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You will design scalable data solutions in GCP, guide the engineering pod, promote development standards and support the team throughout the Agile development process.\nYour tasks\nProvide technical leadership for data migration projects, including solution design, approach and estimation \nDesign and develop scalable data pipelines using GCP, PySpark and Scala \nProvide guidance on environment setup, system architecture and cloud design patterns \nImplement solutions focused on performance, scalability, availability, accuracy and monitoring \nPromote coding standards, conduct code reviews and support knowledge sharing \nMentor engineers and oversee the technical delivery of the engineering pod \nWork with Business Analysts to ensure requirements are correctly interpreted and implemented \nSupport production environments, troubleshoot issues and communicate findings to development teams \nParticipate in planning sessions, status meetings, sprint reviews and retrospectives \nIdentify opportunities to use AI enablers to improve traditional engineering workflows\nYour skills\nAt least 10 years of experience in software design, data engineering and development in Agile and DevOps environments \nStrong development and solution design experience with PySpark or Scala \nHands-on experience with Google Cloud Platform and building data pipelines in GCP \nExperience with Apache Spark, Spark SQL, Hadoop, YARN, Hive, MapReduce and ETL frameworks \nExperience with Python, SQL, PL/SQL and data integration \nExperience with Apache Airflow or similar scheduling tools \nExperience with REST APIs and RESTful services \nStrong knowledge of Unix and Linux environments \nExperience with Git, GitHub, Jenkins, Ansible and Jira \nExperience with automated testing, deployment and monitoring \nUnderstanding of cloud architecture and cloud design patterns \nAbility to lead an engineering pod and guide the work of other engineers \nAbility to work autonomously and act as a technical 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