AWS Infrastructure & Data Engineer

Senior AWS Infrastructure and Data Engineer We’re seeking a highly skilled Senior AWS Infrastructure and Data Engineer to join our team. In this role, you’ll be responsible for designing, building, and maintaining cloud-based data infrastructure and pipelines on AWS. Your work will ensure our data systems are scalable, secure, and efficient—empowering our analytics and business intelligence teams to extract meaningful insights. We are not able to provide sponsorship. The ideal candidate brings deep expertise in AWS services across infrastructure and data, a strong foundation in data engineering principles, and a passion for automation and best practices. Responsibilities • Design and architect scalable, reliable data infrastructure using AWS services such as EC2, S3, RDS, Redshift, and Lambda. • Build and maintain robust ETL/ELT pipelines using AWS Glue, DataSync, and other relevant tools to ingest, transform, and load data from various sources. • Implement and manage data lakes and data warehouses, ensuring data quality, governance, and security. • Develop and deploy Infrastructure as Code (IaC) using Terraform or CloudFormation to automate AWS resource provisioning. • Monitor and optimize performance, cost, and security of the AWS data environment. • Collaborate with data scientists, analysts, and engineers to understand data needs and deliver effective solutions. • Troubleshoot and resolve issues related to data pipelines, infrastructure, and performance. • Stay current with the latest AWS services and industry best practices. Requirements • 5+ years of experience in a similar role with a strong focus on AWS and data engineering. • Proven expertise in core AWS services including S3, EC2, Lambda, RDS, Redshift, Glue, and Step Functions. • Proficiency in at least one scripting language (e.g., Python). • Extensive experience with Infrastructure as Code (IaC), especially Terraform. • Solid understanding of database concepts, data warehousing, and ETL/ELT processes. • Familiarity with version control systems (e.g., Git). • Strong problem-solving skills and ability to work independently and collaboratively. • Excellent communication skills for working with both technical and non-technical stakeholders. Nice to Have • AWS Professional certifications (e.g., AWS Certified Data Analytics – Specialty, AWS Certified Solutions Architect – Professional). • Experience with big data technologies such as Spark, Hadoop, or Snowflake. • Familiarity with CI/CD pipelines (e.g., Jenkins, GitHub Actions). • Knowledge of containerization technologies (e.g., Docker, Kubernetes). • Experience with stream processing tools (e.g., Kinesis, Kafka).