Software Engineer, Data (Platform)

About the role

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences.

As a Software Engineer, Data, you will design, build, and operate the next generation of our 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.

How you’ll measure success:

- Data reliability & SLAs: % successful pipeline runs, adherence to freshness SLAs for core datasets, and reduction in data-related incidents impacting stakeholders for the pipelines and datasets you own.

- 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 from request to production.

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.