Sr. Data Engineer Job New York New York USA,Software Development

Location: New York

Growth-stage company is building a new class of AI-native platform where data is the product. The system processes millions of structured and unstructured outputs daily across a rapidly growing set of external sources, and the underlying data infrastructure directly determines product reliability, correctness, and user trust.

The company is forming its first dedicated data function. This role will define how ingestion, processing, and data quality systems are architected and operated decisions made here will shape the data platform for years, with direct impact on product velocity and customer experience.

What You’ll Do:

Own the architecture and reliability of a multi-source ingestion platform operating at high throughput and increasing scale
Design and evolve distributed data systems that support asynchronous processing, fault tolerance, and horizontal scalability
Define and enforce data contracts across ingestion, transformation, and serving layers to ensure end-to-end correctness
Establish best practices for pipeline observability, including monitoring, alerting, and system health tracking
Drive performance improvements across ingestion and processing layers, ensuring throughput stays ahead of product demand
Partner with product and engineering leadership to ensure data systems are designed proactively for upcoming features
Set technical direction for the data platform and mentor engineers as the team grows

Where You’ll Work in the Stack:

Ingestion: resilient, multi-provider data collection and normalization
Processing: distributed pipelines, async job orchestration, and transformation logic
Storage: columnar systems and query optimization for large-scale analytics
Serving: tight integration with application systems and product features
Observability: system-wide monitoring, alerting, and debugging infrastructure

What We’re Looking For:

Deep experience designing and operating production data systems at scale, including ingestion, ETL, and distributed processing
Strong expertise with modern data infrastructure, including columnar databases (e.g., Click House or similar)
Proven track record owning system reliability, data quality, and observability in production environments
Experience working with external data sources, APIs, or scraping systems at scale
Comfort operating close to the application layer and understanding how data systems power user-facing features
Strong engineering fundamentals (Python or similar; experience with distributed systems required)
Ability to lead technical direction and influence system design across teams

Signals We’re Especially Excited About:

You’ve owned data platforms where correctness and latency directly impacted customers
You’ve built high-throughput systems with strict reliability and completeness requirements
You’ve designed observability systems that provide real-time insight into system health
You’ve operated in early-stage environments and built systems from first principles
You’ve led or mentored engineers while remaining deeply hands-on

Why This Role:

Define the data foundation for a rapidly scaling AI-native product
High ownership across architecture, reliability, and long-term system design
Direct impact on customer-facing product quality and trust
Opportunity to build and shape a data function from the ground up
Close collaboration with experienced founders and engineering leadership

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