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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer, Data - **Company:** CLEAR - Corporate - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $225,000.0 - $300,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Continuous Integration, Information Engineering, Data Integrity, Data Systems, Data Warehousing, Programming Tools, Github, Identity and Access Management, Python (Programming Language), Standard Sql, Software Engineering, Data Streaming, Workflow Management Systems, Pulumi, Snowflake, Apache Spark, Luigi, Integration Frameworks, Apache Kafka, Data Management, Terraform, Jenkins, Databricks - **Published:** May 16, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=fd51f4466b978623 ## About the Role Do you have experience in Terraform?, * 6+ 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), evaluating different data platform integration tooling (e.g. APIs, CDC, batch ingestion, 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) as well as self-service tooling for the other members of the data platform team. * Articulating technical concepts to mixed technical and non-technical audiences, collaborating across teams, mentoring less experienced engineers, and maintaining clarity in ambiguous problem spaces. * Demonstrating curiosity about technology, a bias toward continuous learning, and a strong sense of ownership over architecture, quality, and process improvements in a fast-moving environment. ## Description * 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 critical/high security and dependency findings, improvements in IAM/secrets posture, and 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, and on-time delivery of roadmap initiatives. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Why segmenting your infrastructure into tiers makes your infrastructure design better](https://www.wearedevelopers.com/videos/1960-why-segmenting-your-infrastructure-into-tiers-makes-your-infrastructure-design-better) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Unleashing Potential Across Teams: The Power of Infrastructure as Code](https://www.wearedevelopers.com/videos/930-unleashing-potential-across-teams-the-power-of-infrastructure-as-code) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)