Data Engineer

Data Engineer - Python, AWS, Cloud-Native Pipelines (Hybrid - Richmond, VA)

About the Role
Join a rapidly growing AI and data engineering team as a Data Engineer, developing and supporting cloud-native data ingestion solutions in a hybrid Richmond, VA environment. You will architect, build, and optimize critical data pipelines that enable secure and compliant movement of financial data between enterprise systems and third-party applications. This role offers long-term career growth, hands-on experience with advanced ML Ops and ML engineering tools, and daily collaboration with experts in AWS-native technologies.

Responsibilities

- Design, build, and maintain scalable data pipelines using Python and AWS-native services.
- Develop robust workflows for data ingestion, validation, tokenization, transformation, and publishing.
- Implement and manage distributed data processing solutions using AWS Glue, Spark, Lambda, ECS, and Flink.
- Develop and maintain cloud infrastructure with AWS CDK and Infrastructure as Code best practices.
- Create and execute comprehensive unit, integration, and end-to-end tests to ensure platform stability.
- Monitor, troubleshoot, and resolve production issues across the entire data platform.
- Ensure data security and compliance with enterprise data protection and governance standards.
- Remediate security vulnerabilities and manage platform dependencies.
- Collaborate closely with engineering and platform teams to deliver high-performing, reliable data solutions.
- Contribute to CI/CD pipelines and modern software engineering practices.

Required Skills and Experience

- Proven experience in Python development within enterprise-scale environments.
- Hands-on expertise with AWS services: Lambda, ECS, Kinesis, S3, DynamoDB, IAM, CDK.
- Proficiency with Spark and AWS Glue for large-scale data processing.
- Experience with Git, source control management, and CI/CD pipelines.
- Databricks experience for collaborative analytics and processing.
- Demonstrated success building and supporting cloud-native data pipelines and ingestion frameworks.
- Strong foundation in Infrastructure as Code, data validation, transformation, and data quality.
- In-depth knowledge of secure software development and vulnerability remediation.
- End-to-end testing, system testing, and production deployment support.
- Exceptional troubleshooting skills in distributed systems.

Preferred Skills

- Experience in financial services or regulated data environments.
- Expertise in sensitive data handling, tokenization, or data governance.
- Familiarity with Apache Flink, real-time streaming, and event-driven architectures.
- Knowledge of containerized deployments and orchestration platforms.
- Background in automated testing frameworks and test-driven development.
- AWS certifications (e.g., Solutions Architect Associate, Developer Associate).
- Agile team experience.

Benefits

- Long-term project with significant opportunities for career growth.
- Be part of a dynamic, rapidly expanding team at the forefront of AI data engineering.
- Exposure to ML Ops and ML engineering tools in a fully AWS-native environment.
- Hybrid work flexibility based in Richmond, VA.
- No sponsorship required; all candidates must be authorized to work in the U.S.

How to Apply
Ready to advance your data engineering career? Submit your resume to join an exclusive, high-impact team driving innovation in cloud-native data solutions. Interview times are set, and this opportunity is exclusive to Apex.