Responsibilities Design, develop, and manage our data infrastructure on AWS, with a focus on data warehousing solutions. Write efficient, complex SQL queries for data extraction, transformation, and loading. Utilize DBT for data modelling and transformation. Use Python for data engineering tasks, demonstrating strong work experience in this area. Implement scheduling tools like Airflow, Control M, or shell scripting to automate data processes and workflows.Participate in an Agile environment, adapting quickly to changing priorities and requirements. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Proven expertise in AWS technologies, with a strong understanding of AWS services. Experience in Redshift is optional Experience in data warehousing with a solid grasp of SQL, including ability to write complex queries. Proficiency in Python, demonstrating good work experience in data engineering tasks. Familiarity with scheduling tools like Airflow, Control M, or shell scripting. Excellent communication skills, willing attitude towards learning Preferred technical and professional experience Knowledge of DBT for data modelling and transformation is a plus. Experience with PySpark or Spark is highly desirable. Familiarity with DevOps, CI/CD, and Airflow is beneficial.Experience in Agile environments is a nice-to-have

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