Senior Data Engineer – Data Platform

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.

We're looking for a Senior Data Platform Engineer to join the team building our cloud-native data infrastructure on AWS
. You will be an active contributor to the design and evolution of a platform that serves both data producers and consumers, providing reusable, self-service capabilities for ingestion, curation, aggregation, governance, access interfaces, and observability. This is a platform engineering role: the solutions you build are generic, shared infrastructure, not one-off pipelines.

• Contribute to the design and implementation of
  reusable ETL pipeline templates,scalable, serverless, and event-driven for processing and transforming large datasets from diverse sources
• Help build reusable, self-service platform components that abstract infrastructure complexity for data producers and consumers.
• Define and evolve
  standards of data contracts
  and pipeline configuration schemas that standardize how teams onboard to the platform.
• Implement
  data lineage tracking
  , and observability tooling to give producers and operators full visibility into platform health.
• Implement and maintain
  CI/CD pipelines
  and infrastructure as code using
  Terraform
  .
• Contribute to the technical direction of future platform capabilities, including
  streaming integrations
  , consumption interfaces, data democratization, and
  AI-assisted features
  such as failure remediation and automated contract suggestions.

• Have5+ years
  of professional experience as a Data Engineer or Platform Engineer with strong focus on
  AWS services
• Have a proven track record of contributing to
  production-grade data platforms
  or complex data infrastructure.
• Understand
  data modeling
  and have a solid grasp of
  ETL best practices
  .
• Are proficient in
  Python
  for pipeline development, automation, and scripting.
• Are familiar with data ingestion mechanisms such as
  APIs
  ,
  SFTP
  , or
  message queues
  .
• Have experience building
  event-driven architectures
  and scalable, cloud-native data pipelines.
• Have hands‑on experience with
  streaming platforms
  such as Kafka or AWS Kinesis.
• Implement and maintain data quality rules using Soda Core, integrate quality check results with the
  Data Zone
  catalog, and define the platform's approach to quality failure handling within the pipeline execution flow.
• Are comfortable building and managing infrastructure using
  Terraform
  .
• Use observability tools to monitor logs, performance, and system health.
• Can communicate technical concepts clearly and contribute to cross‑team alignment.
• Cloud AWS:S3, Iceberg, DynamoDB, RDS, Glue, Athena, Lambda, Step Functions, Event Bridge, Transfer Family, Sage Maker, Lake Formation, Data Zone, KMS, IAM Identity Center, SES
• Languages:Python, SQL
• Infrastructure as Code:Terraform
• CI/CD:Jenkins, Git Hub Actions

• Experience with
  Datadog
  for cloud observability and alerting.
• Familiarity with
  AI-assisted developer tools
  such as Claude Code or similar.

If you have a passion for building robust, reusable data infrastructure and want to help shape a platform that will power data-driven products across the organization, we'd love to hear from you!

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