Aws Data Engineer

Role & responsibilities

• Design, build, and maintain cloud-native data pipelines supporting batch and incremental data processing.
• Implement and support a Medallion Architecture (Bronze, Silver, Gold) for enterprise data products.
• Develop and optimize data lake solutions using Amazon S3, Apache Iceberg, AWS Lake Formation, and Amazon Athena.
• Build scalable, secure, and reusable data platform services using Infrastructure as Code (Terraform/Open Tofu).
• Develop data ingestion, transformation, and orchestration processes across multiple data sources.
• Design data models and storage patterns that support analytics, reporting, and downstream applications.
• Implement data governance, access controls, metadata management, and security using AWS Lake Formation.
• Optimize query performance, partitioning strategies, storage formats, and cost efficiency across the data platform.
• Build and maintain CI/CD pipelines for infrastructure, data pipelines, and platform components.
• Develop automation and operational tooling using modern programming languages.
• Collaborate with platform engineering, architecture, security, and application development teams to deliver cloud-native data solutions.
• Troubleshoot production data pipelines, infrastructure, and platform issues.
• Produce technical documentation, architecture diagrams, and implementation standards.
• Mentor junior engineers and promote engineering best practices across the team.

Preferred candidate profile

• 5+ years of experience in Data Engineering, Cloud Engineering, or Data Platform Engineering.
• 3+ years of hands-on AWS experience building cloud-native data platforms.
• Experience implementing Medallion Architecture (Bronze/Silver/Gold) or similar lakehouse patterns.

• Strong experience with:

• Amazon S3
• Amazon Athena
• AWS Lake Formation

• Apache Iceberg

• Experience building scalable ETL/ELT pipelines.
• Strong SQL skills and experience optimizing analytical workloads.
• Experience with Infrastructure as Code using Terraform/Open Tofu.
• Experience implementing CI/CD pipelines for infrastructure and application deployments.
• Experience with Git and modern source control workflows.

• Experience developing automation using one or more of the following:

• Python (preferred)
• Java
• Go

• TypeScript

• Experience with Linux environments (Ubuntu, Red Hat, or CentOS).
• Knowledge of cloud networking and AWS security best practices.
• Experience working in Agile development environments using Jira or Azure DevOps.
• Experience with AWS Glue.
• Experience with Apache Spark or distributed data processing frameworks.
• Experience with event-driven data ingestion architectures.
• Experience with Amazon Redshift and Redshift Spectrum.
• Experience building reusable data platform capabilities and shared engineering frameworks.
• Experience with container technologies including Docker and Kubernetes (Amazon EKS preferred).
• Experience implementing data quality, observability, and monitoring solutions.
• Experience supporting enterprise data governance initiatives.