Systems Engineer, Data Platform & Integrations
New
P
PavilionData platforms
United StatesFull-TimeSenior
Salary185,000 USD per year
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Job Details
- Experience
- 10+ years of experience in systems engineering, data engineering, analytics engineering, backend engineering, or business systems engineering.
- Required Skills
- PostgreSQLPythonSQLSnowflakeRESTful APIs
Requirements
- 10+ years of experience in systems engineering, data engineering, analytics engineering, backend engineering, or business systems engineering.
- Strong Python experience building integrations, pipelines, APIs, automations, or backend services.
- Advanced SQL and experience with modern data warehouses such as Snowflake.
- Prior ownership of operational databases such as AWS RDS, Postgres, or similar.
- Experience building and maintaining integrations with third-party SaaS tools.
- Strong understanding of APIs, webhooks, event-driven workflows, and data synchronization.
- Experience with payment, subscription, and CRM systems.
- Stripe experience or the ability to demonstrate deep understanding of Stripe documentation.
- Strong documentation habits and clear communication with technical and non-technical stakeholders.
- Ability to make sound, scalable architecture decisions in a fast-moving environment.
- Familiarity with the HubSpot API and exposure to subscription businesses are highly preferred.
- Experience creating entitlement systems, access-control logic, or subscription-based products is ideal; ability to incorporate automated workflows is critical.
Responsibilities
- Validate and implement the next chapter of Pavilion’s system architecture.
- Own integrations across core systems, including Stripe, HubSpot, Hivebrite, Slack, Snowflake, and AWS RDS or similar tools.
- Design and maintain data flows between operational, product, sales, and financial systems, including entitlement logic and payment workflows.
- Build and maintain pipelines, transformations, and data models for customer, subscription, payment, revenue, engagement, and access data.
- Own the technical layer for entitlements and customer access logic.
- Support system migrations and new tool implementations, including data mapping, QA, and downstream reporting impacts.
- Improve data quality, freshness, observability, testing, and monitoring.
- Document architecture, source-of-truth decisions, data definitions, and system workflows.
- Partner with Operations, Sales, Marketing, and Finance to translate business needs into technical solutions and write requirements independently.
- Communicate tradeoffs and balance speed with long-term maintainability.
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