paxos - Data Platform Engineer
Requirements
• 8+ years in data engineering or data platform roles • Deep Snowflake administration experience, including RBAC, warehouses, masking policies, governance tags, network policies, storage integrations, and Snowpipe • Production Terraform experience with module development, state management, and import workflows • Terragrunt for multi-environment infrastructure management • Python proficiency • Strong understanding of data governance, security, and compliance best practices • Active use of AI tools (e.g., Claude, Copilot, Cursor) in your engineering workflow — we expect this person to leverage AI as a productivity multiplier • Experience with the Snowflake Terraform provider snowflakedb/snowflake) • AWS infrastructure (S3, IAM, KMS, Secrets Manager) • GitHub Actions CI/CD pipeline development • Apache Iceberg or open table format experience • Data governance and compliance in regulated industries (fintech, banking, payments) • dbt, Dagster, or similar transformation and orchestration tools • Okta/SCIM integration for identity and access management
Responsibilities
• Own data-platform projects end to end: clarify the problem, evaluate alternatives, design the system, implement and roll it out safely, document it, and operate it in production. • Design and evolve reliable, scalable, secure, and cost-effective systems for data ingestion, movement, storage, processing, and access. • Build and improve batch and streaming pipelines and the platform capabilities that support them. • Develop maintainable software, automation, infrastructure, and CI/CD workflows that make platform changes safer and more repeatable. • Improve observability, performance, capacity management, incident response, recovery, and operational readiness across the platform. • Incorporate security, access control, data protection, and governance requirements into platform design and delivery. • Partner with engineering, analytics, security, compliance, and business stakeholders to understand needs, explain tradeoffs, and deliver pragmatic solutions. • Evaluate and learn new technologies as platform needs evolve, applying sound engineering judgment rather than defaulting to a familiar tool. • Use AI tools thoughtfully to accelerate research, design, implementation, testing, debugging, and documentation while critically validating the output. • Contribute to technical direction, design reviews, documentation, and mentoring across a small, high-impact team working across US and India time zones.
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