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Founding Data Engineer Jobs in Secaucus, NJ (NOW HIRING)

Normal Computing

Founding Data Engineer

New York, NY · On-site

$275K - $340K/yr

You'll work alongside verification engineers who set the standard for "good," ML engineers who help tune the generation loop, and pipeline engineers who keep the data organized and versioned. The ...

Embedding VC

Founding Data Engineer

New York, NY · On-site

$125K - $150K/yr

About the role We're hiring a Senior or Staff Data Engineer to build FLORA's data function from scratch. You'd be the first data hire, working directly with the CTO and Head of Product to define what ...

Flora AI

Founding Data Engineer

New York, NY · On-site

$170K - $240K/yr

About the role We're hiring a Senior or Staff Data Engineer to build FLORA's data function from scratch. You'd be the first data hire, working directly with the CTO and Head of Product to define what ...

Shaped

Data Engineer

Brooklyn, NY · Remote

$130K - $200K/yr

You will be a founding engineer working to reliably ingest customer data (both with batch and real-time processing) into our our state-of-the-art AI discovery engine. As one of Shaped's early ...

Shaped

Data Engineer

Brooklyn, NY · On-site

$130K - $200K/yr

You will be a founding engineer working to reliably ingest customer data (both with batch and real-time processing) into our our state-of-the-art AI discovery engine. As one of Shaped's early ...

NxT Level

Founding Backend Engineer

Manhattan, NY · On-site

Founding Senior Backend Engineer (Data Platform / Integrations) Location: New York City - In-Person The Opportunity Our client is hiring a Founding Senior Backend Engineer to own the data platform ...

NxT Level

Founding Backend Engineer

Manhattan, NY

Founding Senior Backend Engineer (Data Platform / Integrations) Location: New York City -- In-Person The Opportunity Our client is hiring a Founding Senior Backend Engineer to own the data platform ...

LHi Group Ltd

Founding Engineer

Manhattan, NY · On-site

$190K - $220K/yr

... scale data processing. What You'll Be Building * Core systems that track AI-generated code ... Founding engineer opportunity with meaningful equity * Solve genuinely difficult engineering ...

Lawrence Harvey

Founding Engineer

New York, NY · On-site

$180K - $225K/yr

... scale data processing. What You'll Be Building * Core systems that track AI-generated code ... Founding engineer opportunity with meaningful equity * Solve genuinely difficult engineering ...

Jampack AI

Founding Engineer - Fullstack

New York, NY · On-site

The Role We're hiring a founding engineer to build the core platform that powers our AI agents and ... Design secure, auditable data models and event-driven pipelines that power our agent workflows

Fuku

Founding Backend Engineer

New York, NY

$160K - $200K/yr

H-1B, O-1, OPT Role Summary As the Founding Backend Engineer, you will own and scale Client's data infrastructure, which powers search, personalization, and recommendations. You will work closely ...

Fuku

Founding Backend Engineer

New York, NY · On-site

$160K - $200K/yr

As the Founding Backend Engineer, you will own and scale Client's data infrastructure, which powers search, personalization, and recommendations. You will work closely with the CTO and ML engineers ...

Ceno Group Inc.

Founding Engineer

New York, NY · On-site

$125K - $200K/yr

This is a founding engineering role focused on backend and infrastructure, and it carries three of ... Strong fluency in a modern backend language (Go, TypeScript, Python, Java, Rust) and data ...

NxT Level

Founding Full Stack Engineer

Manhattan, NY · On-site

$140K - $200K/yr

Founding Product Engineer (Client Search) | AI + B2B SaaS | NYC (In-Person) We're partnering with a ... Background building data-heavy or workflow-driven applications * Previous startup or founding-team ...

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Showing results 1-20

All JobsFounding Data Engineer JobsFounding Data Engineer Jobs in Secaucus, NJ

Founding Data Engineer information

See Secaucus, NJ salary details

$45.2K

$131.9K

$180.5K

How much do founding data engineer jobs pay per year?

As of Jul 26, 2026, the average yearly pay for founding data engineer in Secaucus, NJ is $131,881.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,400.00 and $139,800.00 per year, depending on experience, location, and employer.

What are the unique challenges and opportunities of being a Founding Data Engineer at an early-stage startup?

As a Founding Data Engineer, you'll face the challenge of building data infrastructure from scratch, often with limited resources and evolving requirements. You’ll work closely with founders and cross-functional teams to define data strategies, implement pipelines, and ensure data quality. This role offers significant influence over technical decisions and architecture, and you'll likely wear multiple hats, contributing to both backend engineering and data analytics. The fast-paced environment fosters rapid skill development and provides substantial opportunities for career growth as the company scales.

What are the key skills and qualifications needed to thrive as a Founding Data Engineer, and why are they important?

To thrive as a Founding Data Engineer, you need strong expertise in data architecture, database design, and software engineering, often backed by a degree in computer science or a related field. Familiarity with cloud platforms (like AWS or GCP), ETL frameworks, programming languages (such as Python or Scala), and data warehousing tools is typically required. Exceptional problem-solving, adaptability, and collaboration skills set standout candidates apart in this role. These abilities are crucial for building scalable data systems and shaping the technical foundation of an early-stage company.

What is the difference between Founding Data Engineer vs Data Engineer?

AspectFounding Data EngineerData Engineer
Required CredentialsBachelor's or higher in CS, experience in startup environmentsBachelor's or higher in CS, relevant data tools experience
Work EnvironmentEarly-stage startups, high flexibility, broad responsibilitiesEstablished companies, specialized roles, structured teams
Employer & Industry UsageFounding teams, startups, tech companiesTech firms, finance, healthcare, large organizations
Search & Comparison IntentUnderstanding startup data roles, early-stage responsibilitiesStandard data engineering roles, career progression

The main difference between a Founding Data Engineer and a Data Engineer lies in their work environment and responsibilities. Founding Data Engineers typically work in startups, handling broad tasks and building data infrastructure from scratch, while Data Engineers in established companies focus on specific data pipelines within structured teams. Both roles require similar technical skills and educational backgrounds, but their scope and context differ significantly.

What are Founding Data Engineers?

Founding Data Engineers are among the first technical hires at a startup, responsible for designing, building, and scaling the company's data infrastructure from the ground up. They work closely with founders and early team members to define data architecture, set up data pipelines, and ensure data quality and accessibility for product development and business insights. This role often requires a blend of software engineering, data modeling, and strategic decision-making skills, as well as the flexibility to adapt to rapidly changing priorities in a startup environment.
What are popular job titles related to Founding Data Engineer jobs in Secaucus, NJ? For Founding Data Engineer jobs in Secaucus, NJ, the most frequently searched job titles are:
What job categories do people searching Founding Data Engineer jobs in Secaucus, NJ look for? The top searched job categories for Founding Data Engineer jobs in Secaucus, NJ are:
What cities near Secaucus, NJ are hiring for Founding Data Engineer jobs? Cities near Secaucus, NJ with the most Founding Data Engineer job openings:
Founding Data Engineer jobs near you
Infographic showing various Founding Data Engineer job openings in Secaucus, NJ as of June 2026, with employment types broken down into 66% Full Time, 32% Part Time, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $131,881 per year, or $63.4 per hour.

Founding Data Engineer

Normal Computing

New York, NY • On-site

$275K - $340K/yr

Full-time

Posted 19 days ago

Job description

About Normal Computing
Normal Computing builds silicon that turns thermal noise from an obstacle into a computational resource. Conventional chips spend most of their energy forcing determinism onto physics; ours compute with it. Stochastic, in-memory, asynchronous: the result is 10-100× more AI inference per dollar, per watt.
We co-design the full stack: AI-native EDA systems in production with the world's largest semiconductor companies, and the advanced ASICs they make possible. Backed by $85M+ from the world's leading deep-tech investors and built by scientists, engineers, and operators from the labs that built modern computing.
Normal works as one team across New York, Silicon Valley, London, Copenhagen, and Seoul. We hire people who want the hardest version of their craft, across every discipline, at every seniority.
The Role
Our EDA tool accelerates the design and verification of silicon. It integrates with the engineer's workflow to assist with design, verification, and debugging, and uses AI to generate stimulus, tests, SystemVerilog assertions, and other verification artifacts.
The hard part of that is data, and most of the data we need is not in a format that is easy to train on. The verification artifacts that would teach our agents are locked inside customer environments, paywalled behind standards bodies, or simply never written down. So this role is not primarily about finding data. It's about manufacturing it: generating synthetic training data with programmatic ground truth, mining our own agents' runs for high-quality trajectories, and negotiating access to the real customer data that nothing else can replace. You will own that pipeline end to end and partner directly with the ML/post-training and eval teams, because the only definition of success here is moving a number on our eval harness.
You'll work alongside verification engineers who set the standard for "good," ML engineers who help tune the generation loop, and pipeline engineers who keep the data organized and versioned. The strategy for what data we build, mine, and acquire is yours.
What You'll Own
  • Model Improvement: Your main responsibility is making our models better at hardware design, verification, and EDA workflows by any means possible.
  • The Data Flywheel: Own the data flywheel from our own agent runs: rejection sampling, distillation, and mining eval-passing trajectories so each model round produces the training data for the next.
  • Data Acquisition: Identify, evaluate, and acquire datasets relevant to hardware design, verification, and EDA workflows, with a focus on data that drives measurable improvement in AI agent performance. Assess sources for quality, coverage, licensing, and compliance before ingestion.
  • Quality Standards: Partner with verification engineers to define rubrics, curate golden reference examples, and tell when the pipeline is producing convincing-looking garbage.
  • Pipelines & Lineage: Operate data ingestion pipelines, monitor for quality regressions and coverage gaps, and maintain a structured catalog of data sources, acquisition strategies, and lineage.
  • Customer-Data Partnerships: Negotiate access on customer infrastructure (on-prem and federated), handle redaction and IP constraints, and where direct access isn't possible, build external replicas of a customer's environment that preserve the structure of their specs and testbenches without exposing their IP.
  • Team Building: As the Data team scales, manage engineers across synthetic data, verification SME curation, data infrastructure, and forward-deployed data engineering.

What Makes You a Great Fit
  • You've built or used a data flywheel: model outputs, curated, into the next training round
  • You approach data acquisition as an engineering problem: systematic, measurable, and outcome-driven
  • You've shipped a synthetic-data or training-data pipeline that produced a measurable downstream model improvement you can describe by number, not vibes
  • You can evaluate data quality independently, spotting noise, bias, and gaps without needing someone to tell you what to look for
  • You're comfortable working across multiple technical roles and synthesizing feedback from domain experts, ML engineers, and pipeline engineers
  • You're organized and documentation-minded: you track provenance, ownership, and lineage as a matter of habit

Bonus Points
  • Experience acquiring data from a variety of sources, both paid and unpaid, and managing vendor relationships
  • Familiarity with SystemVerilog, Verilog, and UVM
  • Background in code-model or agent training-data pipelines (e.g. SWE-bench-style data, code-model post-training)
  • Experience with automated data collection, web scraping, or corpus curation at scale
  • Prior work in a startup or fast-moving research environment where the data strategy was still being defined

Equal Employment Opportunity Statement
Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.
Accessibility Accommodations
Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at accommodations@normalcomputing.com.
Privacy Notice
By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Privacy Policy.

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