Data Platform Engineer
4 dni temu
Since the year 2000, OEC has grown globally to more than 1,000 employees with a double-digit revenue increase nearly every year. We provide a lively culture, employee rewards and recognition, and the opportunity to develop and implement innovative technology solutions.
Job Summary
Join us in transforming how vehicles are diagnosed and repaired — faster, smarter, and at scale.
As a Data Platform Engineer, you'll lead the design and evolution of our cloud-native data platform, powering intelligent automotive services with cutting-edge data solutions. In this role, you'll take ownership of building and scaling a modern data platform that delivers critical insights that power fast and accurate vehicle diagnostics and repairs.
The data platform provides capabilities for ingestion, curation, aggregation, governance, access interfaces and observability.
Responsibilities
As a Data Platform Engineer, you will:
- Support a team of data engineers, while staying hands-on in pipeline development and architecture design.
- Build scalable, serverless, event-driven ETL pipelines to process and transform large datasets from diverse sources.
- Optimize AWS resources for performance, cost-efficiency, and security.
- Lead and support migrations from on-premises to AWS-based data platforms.
- Implement and maintain DevOps practices such as CI/CD pipelines, test automation, and infrastructure as code (Terraform).
- Contribute to the planning and design of future data platform development phases.
You Will Be a Great Fit If You
- Have 3+ years of professional experience as a Data Engineer or Platform Engineer with strong focus on AWS services (e.g., S3, Lambda, RDS, Glue and IAM).
- Understand data modeling and have a solid grasp of ETL best practices.
- Are proficient in Python (or .NET/other relevant languages used in serverless environments).
- Are familiar with data ingestion mechanisms such as APIs, SFTP, message queues, or streaming platforms.
- Have experience building event-driven architectures and scalable, cloud-native data pipelines.
- Care about data quality, testing and graceful error handling.
- Use observability tools to monitor logs, performance, and system health (e.g., Datadog).
- Are comfortable building and managing infrastructure using Terraform.
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