As a Cloud Data Engineer at INFUSE, you will be responsible for designing, implementing, and maintaining robust ETL processes on AWS to support our data-driven decision-making. You will work closely with our servers, integrate various web platforms, and perform other data manipulations to ensure data is available, accurate, and actionable. This role requires a blend of technical prowess, problem-solving skills, and a deep understanding of cloud technologies. Key Responsibilities ETL Process Development: Design, develop, and maintain ETL processes on AWS to extract, transform, and load data across various platforms. Server Management: Collaborate with the infrastructure team to manage and optimize servers used for ETL processes. Process Improvement: Continuously update and improve existing ETL processes for better performance, scalability, and reliability. Integration: Integrate data from different web platforms and ensure seamless data flow between different sources and systems. Data Manipulation: Perform data manipulations, and transformations, and ensure data quality for reporting and analytics. Collaboration: Work closely with BI engineers, analysts, and other stakeholders to understand their data needs and provide relevant data solutions. Documentation: Create and maintain comprehensive documentation of ETL processes, data flow diagrams, and integration procedures. Qualifications Experience:
3+ years of experience in data engineering with a focus on cloud technologies. Proven experience with AWS services like S3, Redshift, Glue, Lambda, etc. Technical Skills:
Proficiency in SQL and experience with relational databases. Hands-on experience with ETL tools and frameworks (e.g., Apache Airflow, Talend). Strong scripting skills in Python, SQL, and/or other relevant programming languages. Experience with integration of various web platforms and APIs. Soft Skills:
Strong analytical and problem-solving skills. Excellent communication and teamwork abilities. Self-motivated and able to work independently with minimal supervision. Preferred Qualifications Experience with other cloud platforms (e.g., Azure, Google Cloud). Knowledge of big data technologies (e.g., Hadoop, Spark). Experience with containerization technologies (e.g., Docker, Kubernetes).
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