Job
Description
Roles and Responsibilities: We are looking for an experienced AWS Cloud Data Engineer to join our Data Science & Analytics team to build, optimize, and maintain cloud-based data solutions. The ideal candidate will possess strong technical knowledge in data engineering on AWS, expertise in data integration, pipeline creation, performance optimization, and a strong understanding of DevOps methodologies. Design, develop, and deploy scalable, high-performance data pipelines on AWS and scalable AWS infrastructure solutions. Implement data solutions utilizing AWS services such as S3, Glue, Redshift, EMR, Athena, and Kinesis. Optimize data storage, processing, and query performance to ensure efficiency and reliability. Maintain and enhance ETL processes, including data extraction, transformation, and loading using AWS Glue and Lambda. Ensure data quality, security, compliance, and governance are integrated throughout data workflows. Collaborate closely with data scientists, analysts, and application developers to meet data needs. Monitor and troubleshoot data pipelines and infrastructure proactively. Document data architectures, processes, and standard operating procedures. Document cloud architectures, procedures, and processes clearly and comprehensively. Required Qualifications: Bachelors degree in Computer Science, IT, or a related technical field. 3-5+ years of experience working as a Data Engineer, particularly with AWS cloud infrastructure. AWS Certified Data Engineering - Specialty or similar certifications preferred. Proficiency in AWS data services including S3, Glue, Lambda, Redshift, Athena, Kinesis, and EMR. Strong expertise in building data pipelines using Python, PySpark, or SQL. Experience with big data technologies and frameworks (e.g., Hadoop, Spark). Demonstrable skills with infrastructure-as-code tools like Terraform or CloudFormation. Experience with containerization technologies like Docker and Kubernetes Preferred Qualifications: Familiarity with data lake architectures and Lakehouse implementations. Knowledge of container technologies (Docker, Kubernetes). Experience with data visualization and reporting tools (QuickSight, Tableau, Power BI). Understanding of DevOps methodologies, CI/CD pipelines, and Agile development practices. Competencies: Analytical mindset with a keen attention to detail. Strong problem-solving and troubleshooting capabilities. Excellent collaboration and communication skills. Proactive learner with a commitment to continuous professional development.
