Staff Data Engineer

Role

Staff Data Engineer responsible for technical leadership and long-term vision of Bestow’s data platform. The role drives architecture and standards for data infrastructure, leads MLOps and GenAI infrastructure efforts, mentors engineers, and collaborates cross-functionally to deliver production-grade data pipelines, APIs, and integrations.

Key Responsibilities

• Define and drive the technical roadmap for data infrastructure, establishing architectural patterns and standards.
• Design and implement complex, multi-system data architectures for ingestion, processing, storage, export, and delivery.
• Architect and oversee APIs (REST, GraphQL, gRPC) and API gateway management for internal teams and external partners.
• Lead the evolution of event-driven and API-first architectures, streaming and batch patterns, and real-time ingestion pipelines.
• Leverage Google Cloud Platform services (Cloud Run, Cloud Functions, Vertex AI, App Engine, Cloud Storage, IAM) and Astronomer/Apache Airflow to bring enterprise data workloads to production.
• Establish data governance frameworks, data contracts, quality standards, monitoring, alerting, and automated remediation; participate in on-call rotations.
• Lead MLOps strategy: model deployment, monitoring, governance, and GenAI infrastructure for rapid prototyping with enterprise-grade security and cost management.
• Evaluate and champion emerging technologies and best practices, and implement CI/CD and GitOps for data workflows.
• Mentor data engineers, conduct design reviews, define engineering standards, and participate in hiring and onboarding.

Requirements

• 10+ years in data engineering supporting incoming/outgoing feeds, analytics, and data science teams.
• 5+ years of production-grade Python and advanced Apache Airflow experience.
• 3+ years designing and maintaining production APIs (REST, GraphQL, gRPC), including gateway, rate limiting, auth, and versioning strategies.
• 3+ years leading ML/MLOps initiatives and 3+ years hands-on with Google Cloud Platform services (Cloud Run, Cloud Functions, Vertex AI, Cloud Storage, IAM).
• Deep expertise with columnar databases and SQL optimization (BigQuery, Snowflake, Redshift).
• Experience building end-to-end data pipelines in cloud frameworks (GCP, AWS, Azure) and upstream data coordination via data contracts.
• Experience with CI/CD for data (Docker, CircleCI, dbt, git) and infrastructure-as-code (Terraform, Pulumi) and GitOps practices.
• Expert-level knowledge of data orchestration frameworks (Apache Airflow) to manage SLOs and processing dependencies.
• Experience with streaming/real-time ingestion, containerization and container orchestration, monitoring/alerting, and standard IT security practices (IAM, encryption, key management).
• Demonstrated use of AI coding assistants and familiarity with building Generative AI integrations (enterprise-grade).

Compensation & Location

• Compensation Range: $187,500 - $220,500 (USD)
• Flexible remote/hybrid work; remote and work-from-home options available; office location in Dallas, TX for those who prefer onsite work.