Platform Engineer

Key Responsibilities

• Platform Architecture: Design and maintain the end-to-end technical infrastructure — compute layer, storage layer, orchestration services, caching, and networking.
• Ensure the platform supports multiple product streams with distinct performance profiles (real-time APIs, bulk data delivery, embedded analytics).
• API & Delivery Infrastructure: Build and operate the data delivery layer for external clients — REST APIs for real-time position data, bulk file delivery (SFTP), cloud data sharing (e.g., Snowflake Data Sharing), and webhook-based event notifications. Own API versioning, rate limiting, SLA monitoring, and client onboarding.
• Security & Access Controls: Design and implement role-based (RBAC) and attribute-based (ABAC) access controls to ensure strict client data isolation. Clients accessing their own operational data must never see other clients' data; market-facing products must expose only anonymized/aggregated outputs. Implement encryption at rest and in transit, key management, and secrets handling.
• Multi-Tenancy & Isolation: Architect the platform to support thousands of external users across multiple client organizations, with logical (or physical) data isolation, per-tenant configuration, and audit logging.
• Reliability & Observability: Build monitoring, alerting, and incident response infrastructure. Define and maintain SLAs for uptime, latency, and data freshness. Implement health checks, circuit breakers, and graceful degradation patterns.
• Scalability: Ensure the platform scales from a small number of pilot clients to 2,000+ users without architectural rework. Design for horizontal scaling, auto-provisioning, and cost optimization.
• Compliance & Governance: Support SOC 2 compliance, data residency requirements, and security audit processes. Collaborate with Legal on data-use provisions and technical consent enforcement.
• Collaboration: Work with the Data Engineer (who builds pipelines that run on your platform), the Data Architect (who defines the logical model you physically instantiate), and the Quantitative Director (whose outputs you deliver to clients).

Requirements

• 6+ years in platform engineering, infrastructure engineering, or DevOps/SRE — ideally supporting external-facing data products.
• Expert knowledge of cloud platforms (AWS, Azure, or GCP) — infrastructure-as-code (Terraform, or CloudFormation), containerization (Docker, Kubernetes), and serverless patterns.
• Strong API engineering experience — building, operating, and scaling REST APIs for external commercial consumption. Experience with API gateways, OAuth2/JWT authentication, rate limiting, and versioning.
• Experience designing multi-tenant architectures with strict data isolation and per-client access control.
• Proficiency in at least one systems programming or scripting language (Python, Go, or similar).
• Hands-on experience with observability stacks (Datadog, Prometheus/Grafana, CloudWatch, or equivalent).
• Understanding of security best practices — RBAC/ABAC, encryption, secrets management, SOC 2 controls.
• Experience with cloud data platforms (Snowflake, Databricks) from an infrastructure/provisioning perspective.

Desirable Experience

• Building platforms that serve financial services clients (banks, asset managers, institutional investors).
• Familiarity with data delivery patterns — SFTP, Snowflake Data Sharing, streaming (Kafka/Kinesis), webhooks.
• Experience with cost optimization for cloud infrastructure at scale.
• Understanding of data privacy architectures and how platform controls enforce anonymization/consent rules.
• Prior experience at a data vendor, SaaS company, or fintech where the platform is the product.