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# Data Engineer

- **Company:** Recruiting from Scratch
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Salary:** $130,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Business Analytics Applications, Big Data, Software as a Service, Databases, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Systems, Data Warehousing, Software Debugging, Decision Support Systems, Python (Programming Language), Machine Learning, Software Engineering, SQL Databases, Snowflake, Backend, Data Analytics, Real Time Data, Machine Learning Operations, Data Pipelines
- **Published:** October 17, 2026
- **Apply:** https://www.careerbuilder.com/job-details/data-engineer-san-francisco-ca--eb91db04-0fd5-4e97-8194-3142785ff547

## About the Role

* 3-6+ years of experience in data engineering or backend/data-focused software engineering roles
 * Strong proficiency in SQL and Python for building and maintaining data pipelines
 * Hands-on experience with modern data stack tools (e.g., dbt, Fivetran, Snowflake or similar)
 * Experience designing data models, schemas, and transformations for large-scale datasets
 * Strong understanding of ETL/ELT patterns, data warehousing, and pipeline orchestration
 * Comfortable working cross-functionally with technical and non-technical stakeholders
 * High ownership mindset with the ability to operate in fast-paced, ambiguous environments

Preferred

 * Experience supporting machine learning workflows or analytics platforms
 * Familiarity with event-driven or real-time data pipelines
 * Experience with data governance, lineage, and quality frameworks
 * Background in high-growth startups or data-intensive platforms

## Description

Data EngineerLocation: San Francisco or New York CityCompany Stage: Series C / Late-Stage (AI / Enterprise)Office Type: Onsite (5 Days a Week)Salary: $130,000 - $400,000 + EquityCompany DescriptionThis high-growth AI company is building the infrastructure that powers how human expertise is leveraged to train and improve frontier AI systems. With a global network of tens of thousands of experts and partnerships with leading AI labs and enterprises, the platform operates at massive scale-enabling real-world workflows that directly shape the future of AI. Backed by top-tier investors and operating profitably, the company is focused on scaling its data and infrastructure to support rapid growth and increasingly complex use cases.What You Will DoBuild and maintain robust data pipelines to ingest, transform, and unify data from diverse sources (databases, SaaS tools, analytics platforms)Design and implement data models and transformations using dbt to create clean, reliable, production-ready datasetsDevelop scalable ETL/ELT workflows using modern data stack tools (e.g., Fivetran, dbt, SQL, Python)Ensure high data reliability, availability, and timeliness across the entire data lifecyclePartner closely with data science, engineering, product, and business teams to support data-driven decision makingOwn data quality and monitoring, implementing validation, alerting, and debugging processesContinuously improve pipeline performance, scalability, and observabilityIdeal Background3-6+ years of experience in data engineering or backend/data-focused software engineering rolesStrong proficiency in SQL and Python for building and maintaining data pipelinesHands-on experience with modern data stack tools (e.g., dbt, Fivetran, Snowflake or similar)Experience designing data models, schemas, and transformations for large-scale datasetsStrong understanding of ETL/ELT patterns, data warehousing, and pipeline orchestrationComfortable working cross-functionally with technical and non-technical stakeholdersHigh ownership mindset with the ability to operate in fast-paced, ambiguous environmentsPreferredExperience supporting machine learning workflows or analytics platformsFamiliarity with event-driven or real-time data pipelinesExperience with data governance, lineage, and quality frameworksBackground in high-growth startups or data-intensive platformsCompensation and BenefitsBase salary: $130K - $400K + meaningful equityPerformance-based bonusesRelocation support and housing stipendMonthly meal and wellness stipendsPremium health, dental, and vision coverageFitness membership and additional lifestyle perksHigh-impact role supporting critical data infrastructure for AI systems at scaleThis role is ideal for engineers who enjoy owning data systems end-to-end-building the pipelines, models, and infrastructure that power decision-making, machine learning, and core product functionality at scale.
Data EngineerLocation: San Francisco or New York CityCompany Stage: Series C / Late-Stage (AI / Enterprise)Office Type: Onsite (5 Days a Week)Salary: $130,000 - $400,000 + EquityCompany DescriptionThis high-growth AI company is building the infrastructure that powers how human expertise is leveraged to train and improve frontier AI systems. With a global network of tens of thousands of experts and partnerships with leading AI labs and enterprises, the platform operates at massive scale-enabling real-world workflows that directly shape the future of AI. Backed by top-tier investors and operating profitably, the company is focused on scaling its data and infrastructure to support rapid growth and increasingly complex use cases.What You Will DoBuild and maintain robust data pipelines to ingest, transform, and unify data from diverse sources (databases, SaaS tools, analytics platforms)Design and implement data models and transformations using dbt to create clean, reliable, production-ready datasetsDevelop scalable ETL/ELT workflows using modern data stack tools (e.g., Fivetran, dbt, SQL, Python)Ensure high data reliability, availability, and timeliness across the entire data lifecyclePartner closely with data science, engineering, product, and business teams to support data-driven decision makingOwn data quality and monitoring, implementing validation, alerting, and debugging processesContinuously improve pipeline performance, scalability, and observabilityIdeal Background3-6+ years of experience in data engineering or backend/data-focused software engineering rolesStrong proficiency in SQL and Python for building and maintaining data pipelinesHands-on experience with modern data stack tools (e.g., dbt, Fivetran, Snowflake or similar)Experience designing data models, schemas, and transformations for large-scale datasetsStrong understanding of ETL/ELT patterns, data warehousing, and pipeline orchestrationComfortable working cross-functionally with technical and non-technical stakeholdersHigh ownership mindset with the ability to operate in fast-paced, ambiguous environmentsPreferredExperience supporting machine learning workflows or analytics platformsFamiliarity with event-driven or real-time data pipelinesExperience with data governance, lineage, and quality frameworksBackground in high-growth startups or data-intensive platformsCompensation and BenefitsBase salary: $130K - $400K + meaningful equityPerformance-based bonusesRelocation support and housing stipendMonthly meal and wellness stipendsPremium health, dental, and vision coverageFitness membership and additional lifestyle perksHigh-impact role supporting critical data infrastructure for AI systems at scaleThis role is ideal for engineers who enjoy owning data systems end-to-end-building the pipelines, models, and infrastructure that power decision-making, machine learning, and core product functionality at scale.
Data EngineerLocation: San Francisco or New York CityCompany Stage: Series C / Late-Stage (AI / Enterprise)Office Type: Onsite (5 Days a Week)Salary: $130,000 - $400,000 + EquityCompany DescriptionThis high-growth AI company is building the infrastructure that powers how human expertise is leveraged to train and improve frontier AI systems. With a global network of tens of thousands of experts and partnerships with leading AI labs and enterprises, the platform operates at massive scale-enabling real-world workflows that directly shape the future of AI. Backed by top-tier investors and operating profitably, the company is focused on scaling its data and infrastructure to support rapid growth and increasingly complex use cases.What You Will DoBuild and maintain robust data pipelines to ingest, transform, and unify data from diverse sources (databases, SaaS tools, analytics platforms)Design and implement data models and transformations using dbt to create clean, reliable, production-ready datasetsDevelop scalable ETL/ELT workflows using modern data stack tools (e.g., Fivetran, dbt, SQL, Python)Ensure high data reliability, availability, and timeliness across the entire data lifecyclePartner closely with data science, engineering, product, and business teams to support data-driven decision makingOwn data quality and monitoring, implementing validation, alerting, and debugging processesContinuously improve pipeline performance, scalability, and observabilityIdeal Background3-6+ years of experience in data engineering or backend/data-focused software engineering rolesStrong proficiency in SQL and Python for building and maintaining data pipelinesHands-on experience with modern data stack tools (e.g., dbt, Fivetran, Snowflake or similar)Experience designing data models, schemas, and transformations for large-scale datasetsStrong understanding of ETL/ELT patterns, data warehousing, and pipeline orchestrationComfortable working cross-functionally with technical and non-technical stakeholdersHigh ownership mindset with the ability to operate in fast-paced, ambiguous environmentsPreferredExperience supporting machine learning workflows or analytics platformsFamiliarity with event-driven or real-time data pipelinesExperience with data governance, lineage, and quality frameworksBackground in high-growth startups or data-intensive platformsCompensation and BenefitsBase salary: $130K - $400K + meaningful equityPerformance-based bonusesRelocation support and housing stipendMonthly meal and wellness stipendsPremium health, dental, and vision coverageFitness membership and additional lifestyle perksHigh-impact role supporting critical data infrastructure for AI systems at scaleThis role is ideal for engineers who enjoy owning data systems end-to-end-building the pipelines, models, and infrastructure that power decision-making, machine learning, and core product functionality at scale.
Data EngineerLocation: San Francisco or New York CityCompany Stage: Series C / Late-Stage (AI / Enterprise)Office Type: Onsite (5 Days a Week)Salary: $130,000 - $400,000 + EquityCompany DescriptionThis high-growth AI company is building the infrastructure that powers how human expertise is leveraged to train and improve frontier AI systems. With a global network of tens of thousands of experts and partnerships with leading AI labs and enterprises, the platform operates at massive scale-enabling real-world workflows that directly shape the future of AI. Backed by top-tier investors and operating profitably, the company is focused on scaling its data and infrastructure to support rapid growth and increasingly complex use cases.What You Will DoBuild and maintain robust data pipelines to ingest, transform, and unify data from diverse sources (databases, SaaS tools, analytics platforms)Design and implement data models and transformations using dbt to create clean, reliable, production-ready datasetsDevelop scalable ETL/ELT workflows using modern data stack tools (e.g., Fivetran, dbt, SQL, Python)Ensure high data reliability, availability, and timeliness across the entire data lifecyclePartner closely with data science, engineering, product, and business teams to support data-driven decision makingOwn data quality and monitoring, implementing validation, alerting, and debugging processesContinuously improve pipeline performance, scalability, and observabilityIdeal Background3-6+ years of experience in data engineering or backend/data-focused software engineering rolesStrong proficiency in SQL and Python for building and maintaining data pipelinesHands-on experience with modern data stack tools (e.g., dbt, Fivetran, Snowflake or similar)Experience designing data models, schemas, and transformations for large-scale datasetsStrong understanding of ETL/ELT patterns, data warehousing, and pipeline orchestrationComfortable working cross-functionally with technical and non-technical stakeholdersHigh ownership mindset with the ability to operate in fast-paced, ambiguous environmentsPreferredExperience supporting machine learning workflows or analytics platformsFamiliarity with event-driven or real-time data pipelinesExperience with data governance, lineage, and quality frameworksBackground in high-growth startups or data-intensive platformsCompensation and BenefitsBase salary: $130K - $400K + meaningful equityPerformance-based bonusesRelocation support and housing stipendMonthly meal and wellness stipendsPremium health, dental, and vision coverageFitness membership and additional lifestyle perksHigh-impact role supporting critical data infrastructure for AI systems at scaleThis role is ideal for engineers who enjoy owning data systems end-to-end-building the pipelines, models, and infrastructure that power decision-making, machine learning, and core product functionality at scale.
Data EngineerLocation: San Francisco or New York CityCompany Stage: Series C / Late-Stage (AI / Enterprise)Office Type: Onsite (5 Days a Week)Salary: $130,000 - $400,000 + EquityCompany DescriptionThis high-growth AI company is building the infrastructure that powers how human expertise is leveraged to train and improve frontier AI systems. With a global network of tens of thousands of experts and partnerships with leading AI labs and enterprises, the platform operates at massive scale-enabling real-world workflows that directly shape the future of AI. Backed by top-tier investors and operating profitably, the company is focused on scaling its data and infrastructure to support rapid growth and increasingly complex use cases.What You Will DoBuild and maintain robust data pipelines to ingest, transform, and unify data from diverse sources (databases, SaaS tools, analytics platforms)Design and implement data models and transformations using dbt to create clean, reliable, production-ready datasetsDevelop scalable ETL/ELT workflows using modern data stack tools (e.g., Fivetran, dbt, SQL, Python)Ensure high data reliability, availability, and timeliness across the entire data lifecyclePartner closely with data science, engineering, product, and business teams to support data-driven decision makingOwn data quality and monitoring, implementing validation, alerting, and debugging processesContinuously improve pipeline performance, scalability, and observabilityIdeal Background3-6+ years of experience in data engineering or backend/data-focused software engineering rolesStrong proficiency in SQL and Python for building and maintaining data pipelinesHands-on experience with modern data stack tools (e.g., dbt, Fivetran, Snowflake or similar)Experience designing data models, schemas, and transformations for large-scale datasetsStrong understanding of ETL/ELT patterns, data warehousing, and pipeline orchestrationComfortable working cross-functionally with technical and non-technical stakeholdersHigh ownership mindset with the ability to operate in fast-paced, ambiguous environmentsPreferredExperience supporting machine learning workflows or analytics platformsFamiliarity with event-driven or real-time data pipelinesExperience with data governance, lineage, and quality frameworksBackground in high-growth startups or data-intensive platformsCompensation and BenefitsBase salary: $130K - $400K + meaningful equityPerformance-based bonusesRelocation support and housing stipendMonthly meal and wellness stipendsPremium health, dental, and vision coverageFitness membership and additional lifestyle perksHigh-impact role supporting critical data infrastructure for AI systems at scaleThis role is ideal for engineers who enjoy owning data systems end-to-end-building the pipelines, models, and infrastructure that power decision-making, machine learning, and core product functionality at scale.
Data EngineerLocation: San Francisco or New York CityCompany Stage: Series C / Late-Stage (AI / Enterprise)Office Type: Onsite (5 Days a Week)Salary: $130,000 - $400,000 + EquityCompany DescriptionThis high-growth AI company is building the infrastructure that powers how human expertise is leveraged to train and improve frontier AI systems. With a global network of tens of thousands of experts and partnerships with leading AI labs and enterprises, the platform operates at massive scale-enabling real-world workflows that directly shape the future of AI. Backed by top-tier investors and operating profitably, the company is focused on scaling its data and infrastructure to support rapid growth and increasingly complex use cases.What You Will DoBuild and maintain robust data pipelines to ingest, transform, and unify data from diverse sources (databases, SaaS tools, analytics platforms)Design and implement data models and transformations using dbt to create clean, reliable, production-ready datasetsDevelop scalable ETL/ELT workflows using modern data stack tools (e.g., Fivetran, dbt, SQL, Python)Ensure high data reliability, availability, and timeliness across the entire data lifecyclePartner closely with data science, engineering, product, and business teams to support data-driven decision makingOwn data quality and monitoring, implementing validation, alerting, and debugging processesContinuously improve pipeline performance, scalability, and observabilityIdeal Background3-6+ years of experience in data engineering or backend/data-focused software engineering rolesStrong proficiency in SQL and Python for building and maintaining data pipelinesHands-on experience with modern data stack tools (e.g., dbt, Fivetran, Snowflake or similar)Experience designing data models, schemas, and transformations for large-scale datasetsStrong understanding of ETL/ELT patterns, data warehousing, and pipeline orchestrationComfortable working cross-functionally with technical and non-technical stakeholdersHigh ownership mindset with the ability to operate in fast-paced, ambiguous environmentsPreferredExperience supporting machine learning workflows or analytics platformsFamiliarity with event-driven or real-time data pipelinesExperience with data governance, lineage, and quality frameworksBackground in high-growth startups or data-intensive platformsCompensation and BenefitsBase salary: $130K - $400K + meaningful equityPerformance-based bonusesRelocation support and housing stipendMonthly meal and wellness stipendsPremium health, dental, and vision coverageFitness membership and additional lifestyle perksHigh-impact role supporting critical data infrastructure for AI systems at scaleThis role is ideal for engineers who enjoy owning data systems end-to-end-building the pipelines, models, and infrastructure that power decision-making, machine learning, and core product functionality at scale.