AWS Data Engineer

Overview In this hands-on role you will build and operate an AWS-based data platform that supports an enterprise analytics environment. You will focus on pipelines, orchestration, and cloud infrastructure rather than dashboards or analysis. You’ll translate analytics needs into scalable ETL/ELT solutions and maintain reliable, secure, and cost-efficient data workflows. You will work across AWS services to ensure pipeline health, troubleshoot issues, and document runbooks. This role offers the opportunity to shape a growing platform that enables data-driven decision making at scale. ResponsibilitiesBuild and maintain an AWS-based data platform and Amazon Redshift environmentCode and build data pipelines using Python, dbt, and AWS LambdaWork with S3, Glue, Step Functions, IAM, and CloudWatch to support data workflowsDevelop ETL/ELT processes and data transformation workflowsMonitor pipeline health, troubleshoot failures, latency, and infrastructure issuesBuild for reliability, scalability, security, and cloud cost efficiencySupport data ingestion into the warehouse environmentMaintain data-flow documentation and operational runbooksTranslate analytics requirements into technical pipeline and infrastructure solutionsRecommend automation and architectural improvements as the platform grows Key requirementsHands-on experience with AWS data services (S3, Glue, Step Functions, IAM, CloudWatch)Proficiency in PythonExperience with dbtExperience building data pipelines and ETL/ELT processesFamiliarity with Amazon Redshift or similar data warehousesAbility to monitor, diagnose, and optimize pipeline performance and costsAbility to document data flows and operational proceduresAbility to translate analytical needs into scalable technical solutionsproblem-solving orientationstrong communication and collaborationdocumentation disciplineAWS data services (S3, Glue, Step Functions, IAM, CloudWatch)Amazon RedshiftPython