Senior AWS Data Engineer – Python / PySpark
APRIDEN is supporting a leading global technology organization in hiring a Senior AWS Data Engineer for a full-time permanent opportunity based on-site in Atlanta, Georgia.The selected candidate will work from the hiring organization’s Atlanta office. An in-person interview in Atlanta is mandatory.Role OverviewWe are seeking a senior, hands-on AWS Data Engineer with extensive Python and big-data development experience. The successful candidate will design, develop and support scalable data-processing pipelines and cloud-native data solutions using Python, PySpark, AWS and modern data-engineering technologies.This position requires strong production experience across AWS data services, distributed data-processing frameworks, API integrations, SQL, infrastructure automation and CI/CD.Key ResponsibilitiesDesign, develop and maintain scalable ETL and ELT data pipelines.Develop production-grade big-data applications using Python, Spark and PySpark.Build and support AWS data solutions using EMR, Glue, Lambda, Redshift and S3.Develop event-driven workflows using AWS Step Functions and Amazon EventBridge.Integrate external and internal data sources through REST APIs and SQL-based interfaces.Perform large-scale data transformation, validation, analysis and quality checks.Optimize Spark jobs, SQL queries and cloud data-processing workloads.Troubleshoot failed pipelines, production incidents and data-quality issues.Implement CI/CD pipelines for data-engineering applications.Provision and manage AWS infrastructure using Terraform.Participate in GitLab-based source-control, build, release and deployment workflows.Collaborate with engineering, platform, infrastructure and business teams.Support secure, reliable and scalable data-platform operations.Required QualificationsAt least 10 years of hands-on Python development experience, including substantial experience developing big-data applications.At least 5 years of hands-on AWS data-engineering experience.Strong production experience with AWS EMR, AWS Glue, AWS Lambda, Amazon Redshift and Amazon S3.Strong hands-on experience with Spark or PySpark.Experience with Hadoop or AWS EMR and Hive.Advanced SQL development and query-optimization experience.Experience building scalable data-manipulation and transformation workflows.Experience developing REST API integrations.Hands-on experience with AWS Step Functions and Amazon EventBridge.Strong experience designing ETL and ELT pipelines.Hands-on experience implementing CI/CD pipelines.Hands-on Terraform experience.Experience using GitLab for source control, build or deployment workflows.Experience troubleshooting production data pipelines and data-quality issues.Strong analytical, problem-solving and communication skills.Preferred QualificationsExperience in banking, mortgage, lending, financial services, capital markets or insurance.Experience working with large regulated datasets.Experience with data governance, data-quality controls and production support.Current residence within commuting distance of Atlanta.Employment and Location RequirementsFull-time permanent employment.On-site work in Atlanta, Georgia.Availability to attend an in-person interview in Atlanta.Must be legally authorized to work in the United States.Employment eligibility, work authorization and any sponsorship requirements will be reviewed during the candidate-screening process.Only candidates whose experience closely aligns with the mandatory requirements will be contacted.