AWS Data Engineer

• Assess existing AWS processes, workflows, integrations, schedules, and dependencies.
• Partner with business and technical stakeholders to understand operational objectives, pain points, and future-state requirements.
• Translate those objectives into technical orchestration and architecture requirements.
• Design and recommend approaches for improving orchestration across complex AWS environments.
• Identify opportunities to simplify dependencies, improve concurrency, reduce processing times, and increase reliability.
• Develop and maintain cloud-based data pipelines and automated workflows.
• Design appropriate monitoring, alerting, error handling, retry, and recovery capabilities.
• Evaluate existing technical designs and recommend improvements based on business value, complexity, cost, scalability, and risk.
• Work collaboratively with engineers, architects, application teams, infrastructure teams, and business partners.
• Support teammates, share expertise, and contribute constructively to technical discussions and problem-solving.
• Create clear technical documentation and architecture recommendations.
• Communicate complex architecture and orchestration concepts clearly to business stakeholders and senior leadership.

• Strong hands-on experience designing and developing data and processing solutions in AWS.
• Hands-on experience working in complex AWS environments with multiple systems, processes, integrations, and dependencies.
• Strong understanding of workflow and process orchestration concepts.
• Hands-on experience designing, implementing, or optimizing automated workflows and processing pipelines.
• Hands-on experience with relevant AWS data, compute, event-driven, and orchestration services.
• Strong Python and/or SQL skills.
• Hands-on experience with distributed processing and cloud-based data architectures.
• Strong understanding of dependency management, scheduling, event-based processing, retries, error handling, and failure recovery.
• Hands-on experience implementing logging, monitoring, alerting, and operational observability.
• Ability to identify bottlenecks, unnecessary dependencies, failure points, and optimization opportunities.
• Ability to evaluate architectural alternatives and make recommendations based on operational and business requirements.
• Demonstrated ability to translate high-level business objectives into technical requirements and solution designs.
• Strong team orientation and ability to collaborate effectively across technical and business teams.
• Strong verbal and written communication skills., * Experience supporting large-scale enterprise AWS environments.
• Experience with AWS-native workflow and orchestration services.
• Experience with event-driven architectures.
• Experience with Apache Airflow or comparable orchestration platforms.
• Experience with distributed data-processing technologies.
• Familiarity with DevOps, CI/CD, and infrastructure automation.
• Experience with cloud performance and cost optimization.
• Strong troubleshooting and root-cause-analysis capabilities.
• Strong architectural judgment and ability to explain technical tradeoffs to non-technical stakeholders.

Skills:

• AWS.
• Python.
• SQL.
• Data Pipelines.
• Orchestration.
• Event-driven Architecture.
• Apache Airflow.
• Distributed Processing.
• Cloud Architecture.
• Observability.

Qualification And Education:

• 6+ years of experience in data engineering or related field.