Data Engineer - VC Backed Startups at Signalfire — Remote

# Join SignalFire’s 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 talentnetwork@signalfire.com.

We’re 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.

## Who Should Join?

We’re 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 company’s 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?

• Submit your application to join SignalFire’s Talent Ecosystem.
• We review applications on an ongoing basis to identify strong candidates.
• If there’s a match, a SignalFire talent partner or a leader from one of our startups may reach out directly.
• No match yet? We’ll keep your profile on file for future Data Engineering roles across our portfolio.