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Founding Data Engineer Jobs (NOW HIRING)

Weyerhauser Co

Data Engineer

Seattle, WA · On-site

$130K - $156K/yr

Sustainability is the founding concept of our business and our values drive every decision to ... About the Role Weyerhaeuser's Data & Analytics team is looking for a Data Engineer to build and ...

Weyerhaeuser Company

Data Engineer

Seattle, WA · On-site

$130K - $156K/yr

Sustainability is the founding concept of our business and our values drive every decision to ... About the Role Weyerhaeuser's Data & Analytics team is looking for a Data Engineer to build and ...

Impact Bridge Consulting

Data Engineer - AI

Dallas, TX

$113K - $136K/yr

Data Engineer - AI Dallas, TX (preferred) | Hybrid (Bishop Arts preferred) | Full-time Reports to ... The companys founding engineering team is currently focused on building higher-level AI systems ...

Knit Health

Data Engineer II

San Francisco, CA · On-site

$134K - $162K/yr

Knit is led by a founding team from the University of California Berkeley who have developed a ... What you'll do As a Data Engineer II, you'll be a foundational member of a small, high-impact team ...

Chobani

Staff Data Engineer

MN · Remote

$117K - $140K/yr

Summary The Staff Data Engineer is responsible for building, maintaining and improving data ... has been since its founding in 2005 byHamdi Ulukaya, an immigrant to the U.S. The Company ...

SRP

Principal Data Engineer

Tempe, AZ · On-site

Since its founding in 1903, SRP has fostered a culture of stewardship and customer service ... In addition, the Principal Data Engineer has the added responsibility of defining and guiding the ...

Salt River Project

Principal Data Engineer

Tempe, AZ · On-site

Since its founding in 1903, SRP has fostered a culture of stewardship and customer service ... In addition, the Principal Data Engineer has the added responsibility of defining and guiding the ...

EffectiveAI

Data Product Engineer

San Francisco, CA · On-site

$210K - $270K/yr

What You'll Do As a Founding Data Product Engineer, you will be a crucial part of our initial team, playing a pivotal role in designing and building from the ground up the layer through which ...

Qventus

Senior Data Engineer

$108K - $147K/yr

We're inspired to work with healthcare leaders on our founding vision and unlock world-class medicine through world-class operations. #LI-MB1 Qventus is looking for a Senior Data Engineer to pioneer ...

Rightway

Data Engineer III

Miami, FL

$125K - $150K/yr

We are seeking a full-time Data Engineer III to join our team and define and deploy mission ... Since its founding in 2017, Rightway has raised over $200mm from investors including Khosla ...

Vori, Inc

Forward Deployed Data Engineer

San Francisco, CA · On-site

$134K - $162K/yr

As one of the Founding Forward Deployed Data Engineers , you won't just be implementing processes-you'll be defining them from the ground up . You'll create the playbooks, data pipelines, and ...

Syndesus, Inc.

Senior Data Engineer

New York, NY · On-site

$116K - $157K/yr

About the Role As our client's founding Senior Data Engineer, you'll redefine how the company uses data to broaden access to credit -- not by patching what already exists, but by unlocking what ...

Evio

Data Engineer (Remote)

Denver, CO · Remote

$117K - $141K/yr

In 2025, Wellmark joined as Evio's first non-founding investor and sixth owner health plan. Each ... Provide technical guidance and mentorship within the data engineering team and foster a ...

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 ...

Evio

Data Engineer (Remote)

$117K - $140K/yr

In 2025, Wellmark joined as Evio's first non-founding investor and sixth owner health plan. Each ... We are seeking an experienced Data Engineer who wants to build reliable, scalable systems to bring ...

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All JobsFounding Data Engineer Jobs

Founding Data Engineer information

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$44.5K

$129.7K

$177.5K

How much do founding data engineer jobs pay per year?

As of Jul 10, 2026, the average yearly pay for founding data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 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.
More about Founding Data Engineer jobs
What cities are hiring for Founding Data Engineer jobs? Cities with the most Founding Data Engineer job openings:
What states have the most Founding Data Engineer jobs? States with the most job openings for Founding Data Engineer jobs include:
What job categories do people searching Founding Data Engineer jobs look for? The top searched job categories for Founding Data Engineer jobs are:
Founding Data Engineer jobs near you
Infographic showing various Founding Data Engineer job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Data Engineer

Weyerhauser Co

Seattle, WA • On-site

$130K - $156K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 17 days ago

Job description

About Weyerhaeuser
At Weyerhaeuser, we are the world's premier timber, land, and forest products company. Sustainability is the founding concept of our business and our values drive every decision to ensure we continue to lead the forestry industry in sustainability practices. And we know about sustainability - we led it in the forestry industry when we planted our first seedling by hand in 1938. We recognize that our success is dependent on the success of our people. For over 125 years, our Weyerhaeuser team has been making a difference in the world - from the seedlings we plant, to the forests and trees we nurture, we ensure every acre is managed with diligence, patience and pride. That's the Weyerhaeuser way.
About the Role
Weyerhaeuser's Data & Analytics team is looking for a Data Engineer to build and operate the data platform that powers reporting, analytics, and AI across the enterprise. This hands-on role focuses on building scalable, reliable, well-governed pipelines that move data. We invest heavily in template- and metadata-driven patterns, so onboarding a new source is a configuration exercise, not a net-new build.
We expect engineers to use AI as a force multiplier - both in how we build the platform (LLM-assisted development, testing, and documentation) and in what we deliver from it (AI-ready data products grounded in well-modeled sources). This role partners closely with source-system owners, analytics engineers, data scientists, and data analysts. It's well suited for someone who thrives in a fast-paced environment, has strong opinions about data quality and pipeline reliability, and is energized by building scalable foundations rather than one-off integrations.
Responsibilities
Ingestion & Integration
  • Design and maintain ingestion pipelines that move data from SAP, relational databases, flat files, REST APIs, message queues, and SaaS applications into our data lake/Snowflake.
  • Extend our metadata-driven and template-driven ADF pipeline frameworks so onboarding a new source is a configuration exercise - schema mapping, validation, and config, not handwritten pipelines.
  • Develop Python-based Azure Functions for custom ingestion logic, REST API integrations, paging/retry handling, and schema reconciliation.
  • Implement reliable full and incremental data load patterns - watermarking, CDC, late-arriving data, and replayable backfills.
Modeling & Transformation
  • Land and preserve history of raw data in the Azure data lake or Snowflake (bronze), then build dbt models that conform, deduplicate, standardize, and enrich it into clean silver datasets.
  • Partner with analytics engineers and data analysts to build dimensional models and semantic views that enable AI-ready datasets.
Orchestration & Reliability
  • Orchestrate end-to-end workflows in Azure Data Factory - dependencies, parameterization, retries, dynamic parallelism, and error handling for complex multi-source pipelines.
  • Build monitoring, alerting, and own incident response - triage, root-cause analysis, and backfills, including occasional off-hours coverage for critical loads.
  • Tune pipelines and Snowflake workloads for performance and cost
Data Quality, Security & Governance
  • Implement data quality rules - schema validation, completeness, freshness, business-rule checks, and anomaly detection - wired into pipelines.
  • Apply security and compliance best practices and contribute to lineage, metadata, and catalog efforts.
Platform & Engineering Practices
  • Partner with Data Platform Engineers on Terraform-managed cloud resources, and CICD pipelines.
  • Drive engineering best practices - version control, testing, documentation, observability, and document pipelines, schemas, contracts, and runbooks so the platform is supportable by the broader team.
  • Mentor junior engineers, contribute to design reviews, and help evaluate new tools and patterns. Contribute to code reviews.
AI Enablement
  • Skilled in the use of AI assistants and LLM-powered tools to accelerate development, generate and improve tests, and produce or maintain documentation.
Collaboration
  • Partner with analytics engineers, data analysts, and data scientists to translate requirements into reliable raw data pipelines they can model into downstream products.
  • Communicate technical concepts and trade-offs clearly to both technical and non-technical audiences.

Qualifications
What You'll Have
Required
  • Bachelor's degree in Computer Science, Information Systems, Engineering
  • 4+ years of hands-on data engineering experience building and operating production data pipelines.
  • Strong proficiency in SQL (including performance tuning) and Python (readable, testable, maintainable code).
  • Production experience with a cloud-based ingestion and orchestration platform - Azure Data Factory and Azure Functions preferred, though comparable tools (Fabric Pipelines, AWS Glue/Step Functions, Airflow, Dagster, Prefect, etc.) are acceptable - including parameterized, dynamic, and metadata-driven pipeline patterns.
  • Production experience with dbt or a comparable transformation framework, including building and choosing across materialization patterns (views, tables, incremental, ephemeral, snapshots), test coverage, documentation, and history preservation.
  • Production experience with Snowflake or similar data platform: loading patterns, role-based access, performance tuning, and cost-aware design.
  • Demonstrated experience ingesting from a variety of sources: relational databases, SAP, flat files, REST APIs (JSON/XML), and SaaS applications.
  • Experience implementing incremental/delta load patterns and managing watermarking, CDC, schema evolution, and backfills.
  • Working knowledge of Terraform for provisioning Azure and/or Snowflake resources.
  • Solid understanding of data quality, monitoring, alerting, and operational support practices.
  • Working proficiency with Git, pull-request workflows, and CI/CD pipelines for data - code review, automated testing, and promotion across environments are part of how you ship.
  • AI in your engineering workflow - demonstrated use of AI assistants and LLM-powered tools to accelerate development, generate and improve tests, and produce or maintain documentation.
  • Track record of owning reliability - not just shipping features, but keeping data flowing cleanly over time.
  • Strong communication skills and the ability to work cross-functionally with engineering, analytics, and business teams.
Preferred
  • Exposure or familiarly working with geo-spatial datasets and using geo-spatial functions
  • Exposure or familiarity with Iceberg table structures and operations
  • Experience designing reusable, config-driven ingestion frameworks at scale.
  • Exposure to streaming or near-real-time ingestion (Event Hubs, Kafka, or similar).
  • Familiarity with data governance, lineage, and catalog tooling.
  • Experience with BI tools such as Power BI in a downstream/consumer context.
  • Experience working with manufacturing, supply chain, or forestry/natural-resources data domains.
Location: This role will be based out of our corporate office in Seattle, WA.
What We Offer:
Compensation: This role is eligible for our annual merit-increase program, and we are targeting a salary range of $98,811-$148,217 based on your level of skills, qualifications and experience. You will also be eligible for our Annual Incentive Program, which offers a cash bonus targeting 10% of base pay. Potential plan funding may range from zero to two times that target.
Benefits: When you join our team, you and your dependents will be offered coverage under our comprehensive employee benefits plan, which includes medical, dental, vision, short and long-term disability, and life insurance. We offer a pre-tax Health Savings Account option which includes a company contribution. Other benefit options are also available such as voluntary Long-Term Care and Employee Assistance Programs. We also support personal volunteerism, sponsor a host of diversity networks, promote mentoring, and provide training and development opportunities to help you chart your path to a fulfilling career.
Retirement: Employees are able to enroll in our company's 401k plan, which includes a paid company match in addition to our annual contribution equal to 5% of your base salary.
Paid Time Off or Vacation: We provide eligible employees who are scheduled to work 25 hours or more per week with 3-weeks of paid vacation to use during your first year of employment. In addition, after being employed for six months, eligible employees begin to accrue vacation for future use. We also recognize eleven paid holidays per year, providing a total of 88 holiday hours and paid parental leave for all full-time employees.
Weyerhaeuser is an equal opportunity employer. Inclusion is one of our five core values and we strive to maintain a culture where all our people feel a sense of belonging, opportunity and shared purpose. We are committed to recruiting a diverse workforce and supporting an equitable and inclusive environment that inspires people of all backgrounds to join, stay and thrive with our team.

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