Location: New York City (Hybrid – 3 days per week in-office)

Employment Type: Full-time

Salary: $135,000 – $185,000

Important

• Candidates must live in the New York City metro area and be able to work in-person three days per week
• Relocation is not available for this role
• Candidates must be authorized to work in the United States
• Visa sponsorship is not available

This role is best suited for engineers who have experience working in early-stage or growth-stage startups.

About the Company

TechOpX is partnering with a venture-backed technology company building an AI-native supply chain platform for multi-unit restaurant brands.

The platform helps restaurant operators forecast demand, manage inventory, and optimize purchasing decisions using real operational data from distributors, suppliers, and restaurant systems.

The founding team combines deep supply chain leadership from major restaurant brands with experienced startup engineers who have built and scaled high-growth technology platforms. The company is early-stage, well-funded, and focused on building the core systems that will power the next generation of restaurant operations technology.

The Role

We are hiring a Senior Data Engineer to help build and own the data pipelines that power the platform’s forecasting, inventory intelligence, and analytics capabilities.

You will work closely with the Head of Data & AI/ML and the engineering team to ingest and structure operational data from external systems such as distributors, suppliers, and partner integrations.

You will be the first dedicated data engineering hire working alongside the Head of Data & AI/ML, with significant influence over how the company’s data pipelines and infrastructure evolve as the platform scales.

This role is highly hands-on and involves building reliable pipelines, debugging real-world data issues, and designing systems that turn messy operational data into usable product signals.

Because the company is still early-stage, this role offers significant ownership and influence over how the data infrastructure evolves as the platform grows.

Why This Role Is Interesting

The systems you build will directly power forecasting models and operational decisions used by restaurant operators every day.

You will work with real-world operational data from distributors, suppliers, and restaurant systems, often messy, incomplete, or inconsistent, and design reliable pipelines that turn that data into usable intelligence.

This is an opportunity to help build the company’s core data infrastructure from the ground up, not maintain an existing enterprise data platform.

What You’ll Do

• Design and build scalable data pipelines ingesting operational data from external partners and internal systems
• Integrate and normalize real-world datasets such as distributor exports, supplier feeds, and partner integrations
• Build and maintain reliable ETL/ELT workflows supporting forecasting and analytics systems
• Debug and resolve issues across ingestion pipelines and data workflows
• Develop well-modeled datasets that support analytics and machine learning systems
• Collaborate with the AI/ML team to ensure reliable data inputs for forecasting models
• Work with customers and partners during onboarding to understand and integrate their operational data
• Improve reliability, performance, and maintainability across the data infrastructure

Requirements

• 3–6 years of data engineering experience, ideally in startup or high-growth environments
• Strong production experience with Python and SQL
• Experience building and maintaining data pipelines or ETL workflows
• Experience working with cloud infrastructure (AWS, GCP, or similar platforms)
• Strong understanding of data modeling and pipeline design
• Experience integrating data from external systems, APIs, or partner datasets
• Comfortable working with messy real-world operational data
• Strong communication skills and ability to collaborate across engineering and product teams
• Ability to work in-person in NYC three days per week

Location & Work Authorization

• Must live in the New York City metro area
• Must be able to work onsite three days per week
• Must be authorized to work in the United States
• Visa sponsorship is not available

Nice to Have

• Experience supporting machine learning or forecasting systems
• Experience working with supply chain, logistics, or operational datasets
• Experience with data pipeline orchestration tools (Airflow or similar)
• Experience with customer data onboarding or integrations
• Experience working in early-stage startup environments

What Success Looks Like in 12 Months

• Reliable pipelines ingesting operational data from distributors and partner systems
• Clean, well-modeled datasets powering forecasting and analytics features
• Stable data infrastructure supporting customer onboarding and product growth
• Strong collaboration with engineering and product teams solving real operational data challenges

Who Thrives in This Role

This role tends to work best for engineers who:

• Have worked at early or growth-stage startups
• Enjoy high ownership and autonomy
• Are comfortable working with messy real-world data
• Like solving practical problems that directly impact customers
• Prefer building systems from the ground up rather than maintaining mature enterprise platforms

What’s Offered

• Meaningful equity as an early team member
• Competitive salary
• A small, focused engineering team where your work has immediate impact
• The opportunity to build foundational systems that will scale with the company

About TechOpX

TechOpX partners with high-growth technology companies to help build their engineering teams. Candidates who apply through TechOpX will be introduced directly to the hiring company during the interview process.