Software Engineer, Data (Platform)

About the Role

As a Software Engineer, Data, you will design, build, and operate the next generation of CLEAR's data platform and products—going beyond ID to power a networked digital identity—while keeping member privacy, security, and reliability at the core.

What You'll Do

• Build and operate scalable, reliable data systems and pipelines—from ingestion to modeling to visualization—so Analysts and Engineers can self-service changes in an automated, tested, secure, and high-quality manner.
• Develop and maintain end-to-end data products and pipelines (batch and/or streaming) that collect, clean, transform, and model data, and help operate the infrastructure that powers them to unlock new business use cases and reporting.
• Implement and maintain infrastructure-as-code, CI/CD, and shared developer tooling for data products (e.g., Pulumi/Terraform, GitHub, orchestration tools like Dagster/Airflow) to make it easy and safe for teams to build, test, and ship changes across environments.
• Participate in the data platform on-call rotation and drive incidents to resolution.
• Contribute to security, compliance, and cost posture of the data stack through robust dependency management, IAM and secrets hardening, observability, and performance/cost optimizations.
• Work with product and stakeholders to clarify requirements, contribute to design decisions, and help improve our data platform and processes.

Success Metrics

• Data reliability & SLAs: % successful pipeline runs, adherence to freshness SLAs for core datasets, and reduction in data-related incidents impacting stakeholders.
• Platform quality & efficiency: Timely remediation of security and dependency findings in your areas.
• Delivery throughput & self-service enablement: Lead time from request to production for new data sources and models, reduction in manual engineering support for common workflows, and predictable delivery of well-scoped work.

What You're Great At

• 3+ years of data engineering experience with strong Python and SQL skills, including designing and operating scalable batch and/or streaming data pipelines and orchestration (e.g., Dagster, Airflow, Luigi, dbt, Snowflake, Spark, Kafka, Databricks, or similar technologies).
• Working with cloud-based application development and data platforms, including AWS services, modern data warehouses (e.g., Snowflake), experience with data integration patterns such as APIs, CDC, batch ingestion, or streaming, and collaboration/integration tools like GitHub, Argo, Jenkins, or equivalent.
• Designing and implementing robust data models and transformations in the data warehouse (e.g., dbt, Snowflake) and contributing to shared tooling that helps the team ship safely.
• Articulating technical concepts to mixed technical and non-technical audiences, collaborating across teams, sharing knowledge with teammates, giving thoughtful code reviews, and asking clarifying questions to turn loosely defined requirements into well-scoped work.
• Demonstrating curiosity about technology, a bias toward continuous learning, and a strong sense of ownership over the quality and reliability of the systems you build and operate.