CLEAR
SeniorSoftwareEngineer,Data
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Software Engineer, Data at CLEAR. Skills: data engineering, Python, SQL, data pipelines, data modeling, cloud platforms, data warehouses. design, build, and operate the next generation of our data platform and products. Build and operate scalable, reliable data systems and pipelines – from ingestion to modeling to visualization”
What You'll Achieve.
Data reliability & SLAs; % successful pipeline runs; adherence to freshness SLAs for core datasets; reduction in data-related incidents impacting stakeholders; Platform quality & efficiency; Reduction in critical/high security and dependency findings; improvements in IAM/secrets posture; optimizations to infrastructure and job run costs; Delivery throughput & self-service enablement; Lead time from request to production for new data sources and models; adoption and effectiveness of self-service tooling; reduction in manual engineering support for common workflows; on-time delivery of roadmap initiatives
Industry & Context.
maintaining clarity in ambiguous problem spaces
What They're Looking For.
Must Have
6+ years of data engineering experience, Python skills, SQL skills, designing and operating scalable batch and/or streaming data pipelines and orchestration, working with cloud-based application development and data platforms, modern data warehouses, collaboration/integration tools like GitHub, Argo, Jenkins, or equivalent, designing and implementing robust data models and transformations in the data warehouse, self-service tooling for the other members of the data platform team, articulating technical concepts to mixed technical and non-technical audiences, maintaining clarity in ambiguous problem spaces
Nice to Have
PhD preferred, specific ML framework experience, cloud platform certs
What You'll Do.
and operate the next generation of our data platform and products
Build and operate scalable
reliable data systems and pipelines – from ingestion to modeling to visualization
Develop and maintain end-to-end data products and pipelines (batch and/or streaming) that collect
own the infrastructure that powers them
Implement and maintain infrastructure-as-code
and shared developer tooling for data products
and cost posture of the data stack
Partner with product and other stakeholders to uncover requirements
make architectural decisions
and continuously improve our data platform and processes
How You'll Work.
Team & Collaboration
Partner with product and other stakeholders; collaborating across teams
Communication Scope
Articulating technical concepts to mixed technical and non-technical audiences
Process & Methodology
on-time delivery of roadmap initiatives
Full Job Description
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 38 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 Senior 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 own 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. Improve the security, compliance, and cost posture of the data stack through robust dependency management, IAM and secrets hardening, observability, and performance/cost optimizations. Partner with product and other stakeholders to uncover requirements, make architectural decisions, and continuously 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. Platform quality & efficiency: Reduction in cri
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