Senior Data Engineer

Hyperbolic

. Build Hyperbolic Labs' data infrastructure from 0 to 1 .

Posted 10/5/2026full-timeSan Francisco • California • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and maintaining data infrastructure, including data warehouses and pipelines, while ensuring data reliability and quality. Proficient in designing data models for new products and supporting production systems through monitoring and performance tuning.

Highest-signal resume keywords

Data Warehouse DevelopmentData Pipeline ManagementPostgres ExpertiseData Model DesignAWS Familiarity

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data IngestionData AggregationData ReliabilityData Quality TestingPerformance TuningCI/CD for Data PipelinesLarge Dataset ManagementData GovernanceData LakesDBA Experience

Soft Skills

Strong CommunicationJudgment

Tools & Technologies

AWS EcosystemPostgresData Warehousing ToolsBI ToolsMonitoring Tools

Industry Keywords

Cloud ComputingAI InfrastructureHigh-Growth Technical CompanyTechnical Debt Management

Tech Stack

Tools & technologies

AWSCloudPostgres

About the role

Key responsibilities & impact

Build Hyperbolic Labs' data infrastructure from 0 to 1
Own the data warehouse, data pipelines, and tooling that maintains data health
Ingest and aggregate data from multiple sources
Design data models as new products such as spot and inference launch
Ensure data is reliable, fast, and cost-efficient for analysts and engineering
Support increasing data volume, sources, BI, and reporting needs
Partner with data analysts and engineering
Monitor, troubleshoot, and performance-tune production data systems

Requirements

What you’ll need

Track record of independently building and maintaining a data warehouse that ingests and aggregates data from multiple sources using industry-standard tooling
Experience designing data models for new business lines and products
Experience ensuring data reliability and quality through testing, documentation, and governance
Familiarity with data lakes and data warehouses, and when to use each
Deep knowledge of Postgres, including partitioning, data archival, and moving large datasets
Experience working with large datasets
Experience supporting production systems, including monitoring, troubleshooting, and performance tuning
Strong communication skills and judgment to push back on requests that would add technical debt
Familiarity with the AWS ecosystem (preferred; can be learned on the job)
DBA experience (preferred)
Experience setting up CI/CD for data pipelines (preferred)
Background in GPU infrastructure, cloud computing, or AI infrastructure (preferred)
Experience at an early-stage, high-growth technical company (preferred)
Legally authorized to work in the United States
Must answer whether employment visa sponsorship is required

Benefits

Comp & perks

Equal opportunity employer
Inclusive work environment
Hybrid work arrangement