Data Engineer

We're looking for an AWS-focused Data Engineer who enjoys building scalable cloud data platforms from the ground up. If you've designed data lakes, built ETL pipelines using Glue and Python, optimized Redshift environments, and thrive in a cloud-native ecosystem, we'd love to connect.Successful candidates must be able to provide proof of ability to work in the U.S. without sponsorship. This position is not open to corp-to-corp, subcontractor or independent consulting arrangements. About the RoleWe are seeking a highly skilled Data Engineer with deep AWS experience to help build and scale modern cloud-based data platforms. The ideal candidate is passionate about designing reliable, high-performance data pipelines and leveraging AWS-native technologies to support advanced analytics, machine learning, and business intelligence initiatives.You will partner closely with Data Architects, Analytics teams, Software Engineers, and business stakeholders to develop robust solutions that transform large volumes of raw data into valuable business insights.Key ResponsibilitiesDesign, develop, and maintain scalable data pipelines and ETL/ELT processes in AWS.Build and optimize data lakes and data warehouses using modern cloud architectures.Develop and manage batch and real-time data ingestion frameworks.Create high-quality, reusable data models that support analytics and reporting needs.Implement data quality, governance, security, and monitoring best practices.Optimize performance, scalability, and cost efficiency across AWS data services.Collaborate with business and technical teams to understand data requirements and deliver solutions.Support CI/CD processes and Infrastructure as Code (IaC) initiatives.Troubleshoot production issues and drive continuous improvement of data platforms.Required Qualifications5+ years of Data Engineering experience.3+ years building cloud-native data solutions within AWS.Strong hands-on experience with: AWS GlueAmazon RedshiftAmazon S3AWS LambdaAmazon EMRAWS Step FunctionsAmazon KinesisIAM and AWS Security best practicesAdvanced SQL skills and experience optimizing complex queries.Strong Python development experience for data processing and automation.Experience building ETL/ELT workflows and orchestration frameworks.Strong understanding of data warehousing concepts and dimensional modeling.Experience with version control systems such as Git.Strong problem-solving and communication skills.Preferred QualificationsExperience with Snowflake, Databricks, or Apache Spark.Experience with Terraform or CloudFormation.Knowledge of Kafka and streaming architectures.Experience supporting Machine Learning and AI workloads.AWS Certified Data Engineer, AWS Certified Solutions Architect, or similar certification.Experience working in Agile environments.Technical EnvironmentWe're particularly interested in candidates with experience in:AWS ServicesGlueRedshiftS3LambdaAthenaEMRKinesisStep FunctionsEventBridgeCloudWatchLanguages & ToolsPythonSQLPySparkTerraformGitDockerData TechnologiesData Lake ArchitectureData WarehousingData ModelingETL/ELT DevelopmentStreaming Data PipelinesData GovernanceWhat Makes Someone Successful in This Role?Strong AWS-first engineering mindset.Experience handling large-scale, complex datasets.Passion for automation and operational excellence.Ability to build scalable and maintainable cloud-native solutions.Strong collaboration and communication skills.Nice-to-Have Candidate ProfileYou may be a great fit if you've worked as a:AWS Data EngineerCloud Data EngineerSenior Data EngineerBig Data EngineerData Platform EngineerAnalytics EngineerData Warehouse Engineer  Ref: #208-Rowland Tulsa