# Senior Data Engineer at Hadrian
Own and evolve the data infrastructure that powers critical business intelligence, operational decision-making, and next-generation AI initiatives across the company.
## Your Role
As a Senior Data Engineer at Hadrian, you will own and operate the end-to-end data platform, ensuring reliability, scalability, and performance across the entire data stack. You'll become the primary owner of the data platform while working closely with Engineering, AI, and Hacking teams.
## What you will do
- Own and operate Hadrian's end-to-end data platform, ensuring reliability, scalability, and performance across the entire data stack
- Maintain, troubleshoot, and optimize data integrations, connectors, and pipelines built on Airbyte, dbt, and BigQuery
- Build and evolve data models, transformations, and semantic layers that power analytics, business operations, and AI initiatives
- Drive operational excellence by improving platform reliability, monitoring, and incident response processes
- Partner with stakeholders across Engineering, AI, Security, and Business teams to deliver trusted and actionable data products
- Evaluate and implement modern data platform capabilities, including orchestration, streaming architectures, and Lakehouse technologies
- Build tooling and automation that improves developer and analyst productivity
- Lead strategic data architecture initiatives and help shape the future of Hadrian's AI and MLOps data foundation
## Requirements
- 5+ years of professional Data Engineering experience, ideally in a fast-paced startup or scale-up environment
- Deep hands-on experience with Airbyte and understanding of data replication, connector management, and troubleshooting at scale
- High proficiency with dbt, SQL, and Python, with extensive experience building and maintaining transformation pipelines
- Experience working with GCP and AWS environments, including managing data storage and identity management (IAM)
- Ability to operate independently and take full ownership of a business-critical data platform
- Strong software engineering principles and best practices applied to data infrastructure
- Effective communication with both technical and non-technical stakeholders
## Bonus Skills
- Experience with Kafka, Strimzi, Redis, or other streaming, caching, and in-memory data platforms
- Experience with Lakehouse architectures and Semantic Layer implementations
- Experience with Kubernetes, Helm, Terraform/OpenTofu, or cloud infrastructure automation
- Contributions to open-source data, analytics, or MLOps projects
- Experience deploying or optimizing infrastructure supporting LLM workloads and AI applications