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Executive Startup Data Engineer Jobs in California

Plug

Sr. Data Engineer

Los Angeles, CA · On-site

$123K - $148K/yr

Head of Engineering About Plug Plug is an automotive fintech startup building the marketplace for ... Founded in 2023 and led by former Tesla executives, Plug has facilitated $100M in EV sales since ...

New

Plug Technologies Inc

Sr. Data Engineer

Los Angeles, CA · On-site

$180 - $210/hr

Head of Engineering About Plug Plug is an automotive fintech startup building the marketplace for ... Founded in 2023 and led by former Tesla executives, Plug has facilitated $100M in EV sales since ...

New

Plugmotors

Sr. Data Engineer

Santa Monica, CA · On-site

$180 - $210/hr

Head of Engineering About Plug Plug is an automotive fintech startup building the marketplace for ... Founded in 2023 and led by former Tesla executives, Plug has facilitated $100M in EV sales since ...

New

SupportFinity™

Data Engineer

Redwood City, CA · On-site

$120 - $170/hr

As a fast-growing startup, we are seeking a skilled Data Engineer to help develop data-driven solutions that have real-world impact. We are looking for a Data Engineer with hands-on experience in ...

New

Brevian.ai

Data Engineer

Sunnyvale, CA · On-site

$134K - $161K/yr

Job title Data Engineer Position overview We are looking for an experienced Data Engineer to join ... You get to experience the 0-1 of building a startup, working with talented engineers from ...

Sigma Computing

Data Engineer

San Francisco, CA

$140K - $180K/yr

Data Engineer, Data Platform About the Role We are building out our Data Platform team at Sigma ... Startup experience Qualifications We Want (also, skills you'll learn!) * A drive to continuously ...

Third Wave Automation

Sr. Data Engineer

Union City, CA · On-site

$130K - $156K/yr

Company Description Third Wave Automation is a rapidly growing startup that has demonstrated its ... Excellent presentation skills with the ability to influence executives and engineering leads by ...

Menlo Ventures

Data Engineer I

Laguna Beach, CA · On-site

$85 - $115/hr

YOUR MISSION We are looking for a Data Engineer I who is an exceptional early‑career engineer ... Willing to embrace the pace, ambiguity and challenges of a startup environment PREFERRED ...

Posted today

Third Wave Automation

Sr. Data Engineer

Union City, CA · On-site

$130K - $156K/yr

Company Description Third Wave Automation is a rapidly growing startup that has demonstrated its ... Excellent presentation skills with the ability to influence executives and engineering leads by ...

Waystation AI

Data Engineer

Redwood City, CA · On-site

$120 - $160/hr

You've done real work at an early‑stage startup (seed or Series A), where there was no playbook ... -- a front‑row seat to how an AI‑native company gets built * A real product with real ROI ...

New

Vast

Senior Data Engineer

Long Beach, CA · On-site

$143K - $203K/yr

Provide technical leadership and strategic guidance on data architecture to executive leadership ... Proven ability to balance strategic vision with tactical execution in fast-paced startup ...

Swish Analytics

Data Engineer

San Francisco, CA · On-site +1

$145K/yr

Company Overview Swish Analytics is a sports analytics, betting and fantasy startup building the ... The Swish Analytics team is seeking Data Engineers based in Europe to have a direct impact on the ...

Swish Analytics

Data Engineer

San Francisco, CA · On-site +1

$160K/yr

Company Overview Swish Analytics is a sports analytics, betting and fantasy startup building the ... The Swish Analytics team is seeking Data Engineers to have a direct impact on the infrastructure ...

Rad AI

Data Engineer

San Francisco, CA · On-site

$145K - $200K/yr

We are seeking a Senior Data Engineer to join our engineering team. With our rapid client growth ... Experience working at an early stage startup. * Experience in a HIPAA compliant environment.

Samara Living Inc.

Data Engineer

Redwood City, CA · On-site

$120 - $140/hr

We are growing quickly and are looking to hire a Data Engineer to help scale our data and analytics ... Gain equity ownership in a Series B startup positioned for rapid growth. What We Offer * Salary ...

New

Elve Inc

Data Engineer

Davis, CA · On-site

$85K - $150K/yr

Who is Elve? Elve, Inc is a deep-tech startup in Davis, CA, specializing in the design and ... The Data Engineer will design and deploy data pipelines and databases, statistical analysis tools ...

Sigma Computing

Data Engineer

San Francisco, CA · On-site

$140K - $180K/yr

Data Engineer, Data Platform About the Role We are building out our Data Platform team at Sigma ... Startup experience Qualifications We Want (also, skills you'll learn!) * A drive to continuously ...

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Executive Startup Data Engineer information

What is an executive startup data engineer?

Executive Startup Data Engineers are senior-level professionals who design, build, and oversee data systems and strategies within startup companies. They bridge the gap between technical data engineering and high-level business objectives, often leading small teams or entire data departments. Their responsibilities include developing data pipelines, ensuring data quality, and delivering insights that drive business growth. In a startup environment, they must be both hands-on and strategic, adapting quickly to evolving technical and business needs.

What are the key skills and qualifications needed to thrive as an executive startup data engineer?

To thrive as an Executive Startup Data Engineer, you need expertise in data architecture, advanced analytics, and programming languages like Python or Scala, along with a degree in computer science or a related field. Familiarity with big data platforms (such as Hadoop or Spark), cloud services (like AWS or Google Cloud), and relevant certifications are commonly expected. Leadership, strategic thinking, and effective communication are crucial soft skills for driving data initiatives and collaborating with cross-functional teams in a fast-paced environment. These skills and qualities are vital for building scalable data solutions that support business growth and innovation in a startup setting.

What are some unique challenges executive startup data engineers face when building data infrastructure in early-stage companies?

Executive Startup Data Engineers often encounter the challenge of building scalable and reliable data pipelines from scratch with limited resources and rapidly evolving business needs. They must balance hands-on technical implementation with strategic planning, frequently adapting solutions as product priorities shift. Collaboration with founders, product teams, and business stakeholders is crucial to ensure that data systems align with overall company goals. Additionally, they may be responsible for mentoring junior engineers and setting data governance practices that will scale as the company grows.

What is the difference between Executive Startup Data Engineer vs Data Engineer?

AspectExecutive Startup Data EngineerData Engineer
CredentialsTypically requires advanced degrees (Master's or PhD) in data science, computer science, or related fields, with leadership experienceBachelor's or Master's in CS, data science, or related fields, with technical skills
Work EnvironmentStrategic role in startup leadership, involved in decision-making and high-level planningTechnical role focused on data pipeline development, maintenance, and optimization
Employer & Industry UsageFound in startup leadership teams, tech companies, and data-driven startupsCommon across tech, finance, healthcare, and other data-centric industries

The Executive Startup Data Engineer combines technical expertise with strategic leadership, often involved in guiding data initiatives at a high level. In contrast, a Data Engineer primarily focuses on building and maintaining data infrastructure. The executive role requires more experience, leadership skills, and a broader understanding of business goals, while the Data Engineer emphasizes technical proficiency and data management skills.

What are the most commonly searched types of Startup Data Engineer jobs in California?

The most popular types of Startup Data Engineer jobs in California are:

What are popular job titles related to Executive Startup Data Engineer jobs in California?

For Executive Startup Data Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Executive Startup Data Engineer jobs in California look for?

The top searched job categories for Executive Startup Data Engineer jobs in California are:

What cities in California are hiring for Executive Startup Data Engineer jobs?

Cities in California with the most Executive Startup Data Engineer job openings:

Executive Startup Data Engineer jobs near you

Sr. Data Engineer

Plug

Los Angeles, CA • On-site

$123K - $148K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 3 days ago

New

Key responsibilities

  • Own the dbt transformation layer, including staging, intermediate, and mart models, as well as MetricFlow definitions in the Semantic Layer.

  • Build and maintain ingestion pipelines for OEM partner feeds, dealer data, auction signals, and other data sources, ensuring monitoring and change control.

  • Collaborate with engineering and ML teams to own production data pipelines, support data quality monitoring, and troubleshoot data issues.

Job description

Job Title: Sr. Data Engineer
Team: Engineering
Location: Onsite-Santa Monica, CA
Employment Type: Full-time, Salaried, Exempt
Reports To: Head of Engineering
About Plug
Plug is an automotive fintech startup building the marketplace for electric vehicles. Consumers, dealers, and commercial partners trade in, sell, and auction used EVs through a platform built exclusively for electric, with nothing adapted from legacy automotive.
Consumers can get an instant cash offer in minutes, backed by data-driven pricing, battery state-of-health analysis, with pickup, payment, and title transfer handled end-to-end. Franchise and independent dealers across the United States bid in real time on inventory sourced directly from these consumers, dealers, and commercial partners. The result is a single platform that gives sellers a fast, fair exit and gives dealers a dedicated channel for sourcing used EV inventory.
Founded in 2023 and led by former Tesla executives, Plug has facilitated $100M in EV sales since launch and is backed by a $20M Series A from Lightspeed Venture Partners. We're building the most AI-native startup team in Los Angeles, full of operators, engineers, and ML researchers laying the transaction rails for the used EV market's exponential growth.
Why Plug
  • You'll own a piece of the biggest infrastructure opportunity in automotive.
  • You'll work on a platform built exclusively for EVs, with nothing adapted from legacy automotive.
  • You'll be part of an AI-native company. We're rethinking how work gets done at a fundamental level.
  • You'll work directly with operators who have scaled multi-billion dollar businesses in automotive, EV, and marketplaces.
  • You'll have real ownership, high autonomy, and a direct line to company outcomes.

The Opportunity
We are looking for a Senior Data Engineer to build the governed data layer at the center of Plug's AI-native strategy. Plug runs on Snowflake, dbt, and Fivetran. The infrastructure is in place; the governed layer is still being built. You will own the dbt transformation models and certified metric definitions that the business runs on, the ingestion pipelines that bring in OEM partner feeds, dealer data, auction signals, and HubSpot, and the data foundation that Rain Radar - our production EV pricing model - trains on. You will work with the dbt Semantic Layer as an interface for AI agents to query Plug's data with business context. You report to our head of engineering and work closely with our ML and data engineer.
What You'll Do
Data Platform
  • Own the dbt transformation layer - staging, intermediate, and mart models and MetricFlow definitions in the Semantic Layer - so Plug's business data is queryable by both humans and AI agents with the right business context.
  • Build and maintain the ingestion layer: Fivetran pipelines and HubSpot integration for existing sources, and onboarding new ones - OEM partner APIs, dealer marketing feeds, auction signals, and attribution data - with monitoring and change control.
  • Work with the dbt MCP server and Semantic Layer as Plug's AI agent data interface - no prior MCP experience required, but genuine excitement about the direction where agents replace dashboards as the primary way data is consumed.
  • Maintain the ML feature store alongside our ML and data engineer: training data quality, schema stability, and documentation of the data foundation Rain Radar and future models depend on.
  • Support internal data consumers by surfacing trusted datasets, enabling self-service reporting, and occasionally building reports to meet business needs.

Engineering
  • Collaborate with the engineering team and ML and data engineer; be a strong voice in data architecture decisions and schema design reviews.
  • Use agentic coding tools to write clear, tested, and maintainable transformation logic; bring a "capture everything" instinct to data collection decisions - think proactively about what should be captured, not just what is already specified.
  • Own and contribute to data quality monitoring, alerting, and remediation - the data trust standard the whole organization relies on.
  • Own production data pipelines, participate in incident response, and debug data issues across the stack.
  • Actively raise the data engineering bar through thoughtful code review, documentation, and knowledge sharing - including how you use AI tools.

What You'll Bring
  • 5+ years building production dbt projects end-to-end: staging through mart layers, test coverage, schema change management, and ideally MetricFlow or semantic layer work.
  • Genuine curiosity about AI-native data patterns - excited about the dbt Semantic Layer as an agent interface and building data infrastructure that AI agents query rather than humans navigating dashboards. No experience required; curiosity is.
  • Cross-context ML awareness - has worked near an ML team and understands how upstream data quality decisions affect model training and feature quality, not just analytics accuracy.
  • Snowflake or major cloud warehouse experience - schema design, role-based access control, and performance optimization.
  • Fivetran or comparable ELT tool experience - managing pipelines and onboarding new sources with reliability and observability.
  • Advanced SQL and Python for transformation logic, data quality checks, and pipeline automation.
  • Experience integrating REST APIs and third-party data sources; comfortable with reliability patterns.
  • Operates in agentic development workflows with a high quality bar for AI-generated output.
  • Prior startup or small-team experience with a track record of owning data infrastructure end-to-end. Authorized to work in the US for any employer.

Compensation and Benefits
Annual salary: $180,000 - $210,000
Salary ranges reflect independent, third-party benchmarking against national compensation data. Where an individual's actual offer falls within that range depends on a combination of factors, including relevant experience, specialized skills, training and qualifications, current business needs, and prevailing market conditions. Ranges are reviewed periodically and may be adjusted to reflect changing market conditions.
Benefits & Perks:
  • Health, Vision, and Dental insurance
  • 401(k) plan
  • Daily lunch stipend
  • Equity (based on role and performance)
  • Unlimited PTO
  • Fully stocked kitchen
  • Dog-friendly office
  • Ongoing opportunities for growth and development

This full-time position is based in Sawtelle (between Santa Monica and West Los Angeles) and is an in-person role. We welcome candidates from all locations to apply, provided they are willing to relocate for the role. Relocation assistance will not be provided for successful candidates. Sponsorship not available at this time.
Acknowledgments
Plug is an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We believe diverse teams build better products - full stop.

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