Data Platform Engineer

About the role

We are looking for a Data Platform Engineer to design and build the connective tissue between real-world data systems and our AI platform. You will create scalable, reusable data connectors and transformation layers that make heterogeneous data sources usable for downstream inference. This role sits at the intersection of distributed systems, data infrastructure and applied AI. This role will act in terms of platform primitives, not pipelines.

Key Responsibilities

• Design and build robust connectors across SQL / NoSQL databases, APIs (REST / GraphQL), SaaS platforms (e.g., CRM, storage systems)
• Interpret and model heterogeneous source schemas
• Transform raw source data into formats optimized for AI inference
• Work closely with ML, applied AI and forward deployed teams to define feature expectations
• Collaborate with infrastructure teams to design and ship hosted data pipelines
• Optimize for latency, consistency, and edge constraints
• Design resilient ingestion patterns for unreliable or rate-limited systems
• Build logging, monitoring and debuggability into all integrations

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
• Proven experience building connectors against enterprise systems (SQL/NoSQL databases, Salesforce, S3, REST/GraphQL APIs)
• Systems instinct to architect a platform primitive, not a one-off integration
• Familiarity with inference pipelines or ML-adjacent data preparation preferred
• Comfortable working in a startup environment with ambiguity and evolving requirements