
Data Engineer
Stealth Startup
Job description
Data Engineer
Location:
San Francisco, CA
Work Model:
Onsite
Employment Type:
Full-Time
Industry:
Automotive / EV / AI / Technology
About the Role
As a Data Engineer, you will design, develop, and maintain reliable data pipelines and data systems that enable Data Science, Engineering, Product, and Operations teams to make data-driven decisions.
You will work with large and diverse datasets across customers, vehicles, inventory, pricing, sales, marketplace activity, and operational systems.
What You’ll Do
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Design, build, and maintain scalable ETL/ELT data pipelines
.
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Develop reliable batch and near-real-time data ingestion workflows.
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Integrate data from internal applications, third-party APIs, databases, and other sources.
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Build and maintain data models for analytics, reporting, machine learning, and AI applications.
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Write efficient and maintainable SQL and Python code.
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Work closely with Data Scientists and Software Engineers to provide high-quality datasets for modeling and product development.
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Implement data-quality checks, monitoring, validation, and observability.
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Optimize data pipelines for performance, scalability, reliability, and cost.
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Build and maintain data warehouses and analytical infrastructure.
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Support data governance, security, lineage, and access controls.
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Troubleshoot data pipeline failures and resolve data-quality issues.
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Establish and maintain documentation for datasets, pipelines, and data architecture.
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Help develop the data foundation required for Ever’s AI-native automotive platform.
Required Qualifications
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3+ years of experience in Data Engineering or a closely related role.
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Strong proficiency in Python and SQL
.
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Experience designing and building production-grade ETL/ELT pipelines.
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Experience with relational databases and data warehousing.
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Experience working with cloud-based data infrastructure.
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Strong understanding of data modeling and database design.
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Experience with data quality, validation, monitoring, and pipeline reliability.
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Ability to work effectively with Data Scientists, Software Engineers, Product, and business teams.
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Strong problem-solving and debugging skills.
Preferred Qualifications
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Experience with Snowflake, BigQuery, Redshift, or Databricks
.
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Experience with AWS or another major cloud platform.
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Experience with Airflow, Dagster, Prefect, or similar orchestration tools
.
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Experience with dbt
.
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Experience with Spark or other distributed data-processing technologies.
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Experience building real-time or streaming data pipelines.
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Experience with Kafka or similar event-streaming platforms.
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Experience supporting machine-learning or AI workloads.
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Experience with automotive, e-commerce, marketplace, mobility, or other high-volume transactional data.
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Experience working at an early-stage or high-growth technology company.
What We’re Looking For
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Strong ownership and attention to data reliability.
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Ability to design simple, scalable solutions to complex data problems.
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Strong engineering fundamentals and clean coding practices.
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Comfort working in a fast-moving startup environment.
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Ability to collaborate across technical and business teams.
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Interest in AI, machine learning, automotive technology, and data-driven products