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Open Data Jobs in California (NOW HIRING)

Senior R&D Software Engineer, Fivetran AI

Oakland, CA · On-site

$140K - $185K/yr

About the Role Fivetran and dbt are building the open data infrastructure that powers AI agents you can trust. Fivetran is looking for a Senior R&D Software Engineer to join our fast-growing Fivetran ...

Senior R&D Software Engineer, Fivetran AI

Oakland, CA · On-site

$140K - $185K/yr

About the Role Fivetran and dbt are building the open data infrastructure that powers AI agents you can trust. Fivetran is looking for a Senior R&D Software Engineer to join our fast-growing Fivetran ...

Analytical thinking (there are no pre-existing solutions for the most of the request so candidate should be able to find the way to figure and explain based on open question and the raw data) * Excel ...

Showing results 41-60

Open Data information

See California salary details

$45.4K

$162.9K

$240.3K

How much do open data jobs pay per year?

As of Aug 7, 2026, the average yearly pay for open data in California is $162,857.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,800.00 and $167,800.00 per year, depending on experience, location, and employer.

What is open data?

Open data refers to data that is made publicly available for anyone to access, use, and share without restrictions. It is typically provided by governments, organizations, or institutions in formats that are easy to read and process, such as CSV or JSON files. The goal of open data is to promote transparency, innovation, and informed decision-making by making information freely available to the public. Open data can be used in a variety of fields, including research, journalism, business, and civic engagement.

What is the difference between Open Data vs Data Analyst?

AspectOpen DataData Analyst
Required CredentialsNone specific; open data is publicly availableBachelor's degree in data science, statistics, or related field
Work EnvironmentPublic repositories, government portals, open data platformsCorporate offices, consulting firms, or data teams within organizations
Employer & Industry UsageGovernment agencies, research institutions, NGOsBusinesses, marketing, finance, healthcare sectors
Common Search & Comparison IntentUnderstanding open data sources and accessibilityAnalyzing data to derive insights for decision-making

Open Data involves publicly available datasets used for research, transparency, or public benefit, while Data Analysts interpret and analyze data to support organizational decisions. Both roles require analytical skills, but Data Analysts typically have specialized training and work within private or corporate environments, whereas Open Data focuses on data sharing and accessibility for the public or research purposes.

What are some common challenges faced by professionals working in open data roles when collaborating with different departments?

Professionals in Open Data roles often encounter challenges such as varying data standards across departments, differing levels of data literacy, and concerns about data privacy or security. Building consensus on data sharing protocols and ensuring data quality can require extensive communication and advocacy. Effective Open Data specialists foster collaboration by translating technical concepts into accessible language and working closely with IT, legal, and policy teams to align on best practices and compliance.

What are the key skills and qualifications needed to thrive as an open data specialist, and why are they important?

To thrive as an Open Data Specialist, you need strong data analysis skills, proficiency in data management, and a background in fields such as information science, statistics, or computer science. Familiarity with open data platforms, data visualization tools, and knowledge of data standards or metadata schemas are typically required, along with relevant certifications like Certified Open Data Practitioner. Excellent communication, collaboration, and problem-solving skills help translate complex data findings to diverse audiences and stakeholders. These abilities are crucial for ensuring data transparency, accessibility, and impactful use of open data resources.
What are popular job titles related to Open Data jobs in California? For Open Data jobs in California, the most frequently searched job titles are:
What job categories do people searching Open Data jobs in California look for? The top searched job categories for Open Data jobs in California are:
Infographic showing various Open Data job openings in California as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, 2% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $162,857 per year, or $78.3 per hour.

Senior Staff R&D Software Engineer, Fivetran AI

Fivetran

Oakland, CA • On-site

$140K - $185K/yr

Full-time

Posted 18 days ago


Job description

About Us

Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we're delivering the data infrastructure layer that helps organizations move, transform, and trust their data - from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we're building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It's an exciting time to join us: we're creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites.

About the Role

Fivetran and dbt are building the open data infrastructure that powers AI agents you can trust.

Fivetran is looking for a Senior Staff R&D Software Engineer to join our fast-growing Fivetran AI team. Your data stack was built for humans - but agents are the new primary data consumers, and they have fundamentally different requirements. Agents can't intuit context; it must be explicitly codified, governed, and traceable. We're building the governed context layer that solves this problem: Agents Schema, an open standard for storing agent-ready context directly in the customer's own data warehouse, and Context Builder, the managed service that keeps it filled and fresh.

This role goes well beyond standard engineering. You'll research emerging techniques in the fast-moving AI landscape and bring real product and market understanding to decide which ideas are worth pursuing - and then you'll take what you've learned and ship it as production software. We're looking for a true generalist who is willing and able to wear whatever hat the moment calls for: prototyping a new retrieval technique one week, hardening a backend service the next, then doing SRE or QA work when the team needs it. At this level, you're a trusted expert beyond your own department - your judgment shapes technical direction across Fivetran AI and the teams it depends on, you define your own direction rather than waiting for it, and you execute with the highest level of independence. Fivetran AI operates like a startup within Fivetran, and we need engineers who thrive on that range and ambiguity rather than staying in one lane.

Fivetran is the epitome of data-driven development - our engineering team is focused on building a world class product that:

  • Builds Infrastructure Agents Can Trust - join our mission to deliver the governed context layer that AI agents depend on: accurate semantic definitions, traceable lineage, data contracts, and auditable history baked in from the start.
  • Embraces Open Standards - help build portable, interoperable data infrastructure: Agents Schema, open formats (Iceberg, Delta Lake), MCP-native interfaces, and connector skills that work with any model and any compute.
  • Scales Without Breaking - work to make Fivetran AI efficient at agent scale, where unit costs deflate as volume grows and context retrieval is fast, accurate, and cost-controlled.

We emphasize using no-nonsense tools and take great pride in the simplicity and effectiveness of the systems we build. Our back-end is built on Java, Python, Postgres, and Kubernetes, and our front-end is built on React and TypeScript.

This is a full-time hybrid position based out of our Oakland, CA office. Our hybrid work model offers a blend of remote flexibility and in-person collaboration, including two days in the office each week to connect and build as a team

Technologies You'll Use

Python, Java, SQL, dbt, LLMs (Claude, ChatGPT, Gemini), vector databases, BigQuery / Snowflake / Databricks, MCP protocol, React, TypeScript, Kubernetes

What You'll Do

  • Identify which emerging AI research and techniques are worth pursuing, and set the agenda for Fivetran AI's technical roadmap accordingly
  • Prototype new ideas quickly, then take the ones that prove out and turn them into shipped, production-grade features
  • Define technical direction that spans Fivetran AI and collaborating departments - product, data platform, and go-to-market - resolving architectural tradeoffs that cross department lines
  • Build and maintain both back-end and front-end systems for the Fivetran AI product - from Agents Schema pipelines to the Context Catalog UI
  • Set the long-term technical vision for capabilities like AISQL: natural language to SQL grounded in dbt metric definitions, executed natively against the warehouse
  • Take ownership of production reliability across the platform: on-call rotation, incident response, and SRE work to keep the system trustworthy at scale
  • Set the bar for engineering quality, testing, and QA practices across the department, and do hands-on work yourself when it matters most
  • Use coding agents to automate the repetitive parts of the job, freeing up time for the research and design work that needs a human
  • Define your own priorities and roadmap based on your judgment of what will most move Fivetran AI forward, with minimal oversight
  • Mentor staff and senior engineers, and act as a multiplier for technical judgment across the department
  • Represent Fivetran AI's technical perspective in cross-department planning and strategy discussions
  • Contribute to hiring by participating in and helping shape the interview process

Skills We're Looking For

  • 10+ years of programming experience across Python and/or Java, with the ability to move fluidly between back-end and front-end work
  • Considered a trusted expert beyond your own department, able to exert influence and shape direction with collaborating departments
  • Comfortable reading AI/ML research and turning promising findings into working prototypes, then production systems, at a level that sets direction for others
  • Deep product and market awareness - able to judge which emerging techniques are worth building versus which are hype, and defend that judgment to skeptical stakeholders
  • Track record of defining your own direction and executing it with the highest level of independence, with little need for oversight
  • Experience with SQL and data warehouses (BigQuery, Snowflake, Databricks, or similar)
  • Genuine willingness to work across the full stack: research, backend, frontend, SRE, and QA, as the team's needs demand
  • Writes well-structured, performant code and can dive into unfamiliar codebases to suggest improvements
  • Experience using coding agents or similar AI tooling to speed up day-to-day engineering work
  • Demonstrated ability to mentor senior and staff engineers and influence technical decisions across departments
  • Thrives in a startup-like environment with shifting priorities and a high degree of ownership

Bonus Skills

  • Experience with LLM-powered applications - RAG pipelines, embeddings, evaluation frameworks, or agent frameworks
  • Familiarity with semantic layers - dbt, LookML, Sigma, or similar
  • Experience with the MCP (Model Context Protocol) ecosystem or building AI agent integrations
  • Background in site reliability engineering - monitoring, alerting, incident response
  • Experience in data processing (ETL, ELT) and/or building data connectors
  • Experienced working in a cloud environment utilizing AWS, GCP, Kubernetes, or Docker
  • Contributions to open source AI or data projects

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