Senior Data Engineer
Location: New York City (3 days/week in-office)
Employment Type: Full-time
About Us
We're building an AI-native supply chain operating system for restaurant chains. We use AI to automate planning, inventory management, and spend optimization, driving higher sales, lower COGS, and saving team time. SightlineOS was co-founded by Yusha Hu, who previously led supply chain and procurement teams at Chipotle, sweetgreen, and HelloFresh, and Derrick Staten, who was technical cofounder of The League and an engineer and head of product at Branch as it scaled from zero to a $4B valuation.
The Role
As a Senior Data Engineer, you will own the core data foundation that powers forecasting, inventory intelligence, and financial insights across the platform. You will work closely with AI/ML, product, and full stack engineers to turn raw real-world supply chain data into reliable, scalable systems that customers trust. You will also work directly with customers during implementations to understand their data, troubleshoot issues, and ensure successful onboarding.
This is a high-ownership role where your architectural decisions directly impact model performance, product reliability, and customer outcomes, and where clear communication with both technical and non-technical stakeholders is essential.
You will be reporting to Louis Bensard, Head of AI & ML.
What You'll Do
Design and own scalable data pipelines ingesting high-volume, granular supply chain data
Build and maintain reliable ETL/ELT workflows for forecasting, inventory, and financial use cases
Develop clean, well-modeled datasets that power ML models and customer-facing analytics
Ensure data quality, freshness, observability, and correctness across the platform
Partner with AI/ML engineers to support training, inference, and evaluation workflows
Make architectural decisions that scale with customer growth and data complexity
Improve performance, reliability, and cost efficiency across the data stack
Collaborate directly with founders and customers to understand real operational data needs
Requirements
3-5 years of data engineering experience, ideally at Series A–F startups
Strong experience with Python and SQL in production environments
Hands-on experience building and operating data pipelines at scale
Experience with modern cloud data infrastructure (e.g. AWS, GCP, or similar platforms)
Experience with modern data warehouses and transformation workflows
Strong understanding of data modeling for analytics and machine learning
Ownership mindset with a track record of shipping reliable systems
Clear communicator who collaborates effectively with engineering, product, and clients
Willing to work in-person in NYC 3 days per week
Nice to Have
Experience supporting ML training and forecasting systems
Experience with AWS (e.g. S3, Redshift, Glue, Lambda, IAM)
Background in supply chain, operations, or time-series data
Familiarity with streaming or near-real-time data systems
Experience with data quality, lineage, and observability tools
What We Offer
Meaningful equity as an early team member
Competitive salary
Work on cutting-edge agentic AI applications solving real-world problems
Real ownership and autonomy over technical decisions
Direct access to founders with experience at Chipotle, sweetgreen, HelloFresh and Silicon Valley technology startups
The chance to build foundational technology that will scale with the company
Small, focused team where your impact is immediate and visible
If you’re energized by building core data systems from the ground up with real ownership, startup mindset and want to help modernize how restaurants manage their supply chains, we’d love to talk!