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Data Engineer VC Backed Startups

SignalFire


Job Location:

San Francisco, CA - USA

Monthly Salary: Not provided by the employer
Posted: 7 August 2026 (26 days ago)
Application Deadline: 4 November 2026
Vacancies: 1 Vacancy

Job Summary

Join SignalFires Talent Network for Data Engineer Roles at VC-Backed Startups

This is not an application for a specific job. Instead this is a way to get on the radar of VC-backed startups that are actively hiring Data Engineering talent. If you have any questions please direct inquiries to .

At SignalFire we partner with top early-stage startups that are shaping the future of technology. Our portfolio spans 200 innovative companies across AI cybersecurity healthtech fintech developer tools and enterprise SaaS.

Were looking to connect with exceptional Data Engineers who are excited about building scalable data infrastructure developing reliable pipelines and enabling teams to make better decisions with trusted data.

By joining SignalFires Talent Network your profile will be shared with our portfolio companies giving you visibility into exclusive early-stage opportunities that may not be publicly listed.

Who Should Join

Were looking for engineers who are:

Passionate about building reliable scalable data systems and infrastructure
Experienced in transforming complex datasets into trusted accessible data products
Excited to establish data foundations in fast-moving startup environments
Comfortable partnering with engineering product analytics and machine learning teams
Interested in improving how data is collected modeled governed and used across an organization

Typical Roles & Responsibilities
  • Design build and maintain scalable batch and real-time data pipelines

  • Develop reliable data models transformation workflows and shared datasets for analytics and operational use cases

  • Build and manage cloud-based data warehouses lakehouses and data platforms

  • Integrate data from product customer financial and third-party systems

  • Establish standards for data quality testing lineage observability and documentation

  • Partner with analytics product engineering and business teams to understand data requirements

  • Support machine learning and AI applications by developing dependable training feature and inference data pipelines

  • Improve the performance scalability and cost efficiency of data infrastructure

  • Build self-service tools and frameworks that make data easier to discover and use

  • Implement appropriate access controls privacy safeguards and data-governance practices

  • Troubleshoot pipeline failures data-quality issues and performance bottlenecks

  • Help define the companys broader data architecture and technical roadmap

Common Qualifications

While each startup has its own hiring criteria many Data Engineer roles in our network look for:

  • 3 years of experience in data engineering software engineering analytics engineering or a related technical role

  • Strong programming skills in Python Java Scala or a similar language

  • Advanced proficiency in SQL and experience designing scalable data models

  • Experience building and maintaining production ETL or ELT pipelines

  • Familiarity with cloud platforms such as AWS GCP or Azure

  • Experience with modern data warehouses or lakehouse platforms such as Snowflake BigQuery Redshift or Databricks

  • Knowledge of workflow orchestration transformation and data-quality tooling

  • Understanding of distributed systems data storage formats and batch or streaming architectures

  • Ability to collaborate with technical and non-technical stakeholders to translate business needs into data solutions

  • Strong judgment around reliability scalability governance and infrastructure tradeoffs

  • Experience in venture-backed startups or rapidly scaling technology companies may be preferred

Technologies You Might Work With:
  • Languages: Python SQL Java Scala Go

  • Warehouses & Lakehouses: Snowflake BigQuery Redshift Databricks Delta Lake

  • Pipelines & Transformation: Airflow Dagster Prefect dbt Fivetran Airbyte

  • Streaming & Processing: Kafka Spark Flink Kinesis Pub/Sub

  • Cloud & Infrastructure: AWS GCP Azure Docker Kubernetes Terraform

  • Data Quality & Observability: Great Expectations Monte Carlo Soda DataHub OpenLineage

  • Databases & Storage: PostgreSQL MySQL DynamoDB MongoDB S3

What Happens Next
  1. Submit your application to join SignalFires Talent Ecosystem.

  2. We review applications on an ongoing basis to identify strong candidates.

  3. If theres a match a SignalFire talent partner or a leader from one of our startups may reach out directly.

  4. No match yet Well keep your profile on file for future Data Engineering roles across our portfolio.


Required Experience:

IC