Senior Data Platform Engineer

CoreWeave

. Architect, develop, test, and maintain distributed batch and streaming pipelines that ingest, transform, validate, and deliver structured and semi-structured data across production systems .

Posted 11/10/2026full-timeRemote • United StatesSenior💰 $165,000 - $242,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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

Demonstrates expertise in architecting and developing distributed data pipelines, optimizing workflows, and implementing data models for large-scale analytical workloads. Proficient in programming languages and data transformation technologies, with a strong focus on performance, scalability, and data quality.

Highest-signal resume keywords

Data Pipeline DevelopmentWorkflow Orchestration TechnologiesData Modeling and Storage StrategiesProgramming in Python, Go, Java, or ScalaSQL and Database Performance Optimization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentData TransformationData ModelingSQLPerformance OptimizationDistributed Data ProcessingAutomated TestingVersion ControlContinuous IntegrationTechnical Documentation

Soft Skills

Communication of Technical DesignsCollaboration with Stakeholders

Tools & Technologies

DbtDagsterAirflowLogging SystemsAPIs

Industry Keywords

Data EngineeringData InfrastructureCloud Data WarehousesExport-Control Eligibility

Tech Stack

Tools & technologies

AirflowCloudJavaPythonScalaSQLGo

About the role

Key responsibilities & impact

Architect, develop, test, and maintain distributed batch and streaming pipelines that ingest, transform, validate, and deliver structured and semi-structured data across production systems
Build and optimize workflows using dbt, Dagster, Airflow, or comparable tools
Establish testing, deployment, dependency-management, data-quality, and observability standards for workflows
Design data models, schemas, partitioning strategies, and storage patterns for large-scale analytical workloads
Diagnose and resolve performance, scalability, availability, and cost-efficiency issues within multi-petabyte data environments
Partner with software engineering teams to define event schemas and implement reliable logging, telemetry, and instrumentation
Design metadata, lineage, governance, and semantic-modeling systems for consistent business definitions and secure self-service analytics
Establish data interfaces and platform foundations for internal AI applications
Monitor production systems, troubleshoot incidents, document operational procedures, and participate in an on-call rotation after required onboarding and training
Evaluate architectural alternatives, identify system constraints, and select appropriate data structures, algorithms, database designs, and distributed-processing patterns

Requirements

What you’ll need

Bachelor’s degree or foreign equivalent in Computer Science, Computer Engineering, Data Science, Information Systems, or a closely related technical or quantitative field involving substantial coursework in Engineering
At least five years of progressive professional experience in software engineering, data engineering, data infrastructure, or a closely related occupation
Professional experience designing and implementing production data pipelines and distributed data-processing systems
Professional experience with data transformation or workflow-orchestration technologies such as dbt, Dagster, Airflow, or comparable platforms
Professional experience designing data models, schemas, and storage strategies for large-scale analytical databases or cloud data warehouses
Professional experience programming in Python, Go, Java, Scala, or another general-purpose programming language used to build production data systems
Professional experience with SQL, database performance optimization, data-quality testing, and production monitoring
Knowledge of software-engineering practices, including version control, automated testing, code review, continuous integration, deployment automation, and technical documentation
Knowledge of web-application telemetry, event instrumentation, logging systems, APIs, and distributed-service architecture
Ability to communicate technical designs, risks, and tradeoffs to engineering, data science, analytics, and business stakeholders
Export-control eligibility: U.S. person, eligible to access export-controlled information without required authorization, or eligible and reasonably likely to obtain required authorization

Benefits

Comp & perks

Discretionary bonus
Equity awards
Medical, dental, and vision insurance - 100% paid for by CoreWeave
Company-paid Life Insurance
Voluntary supplemental life insurance
Short and long-term disability insurance
Flexible Spending Account
Health Savings Account
Tuition Reimbursement
Ability to Participate in Employee Stock Purchase Program (ESPP)
Mental Wellness Benefits through Spring Health
Family-Forming support provided by Carrot
Paid Parental Leave
Flexible, full-service childcare support with Kinside
401(k) with a generous employer match
Flexible PTO
Catered lunch each day in our office and data center locations
A casual work environment
A work culture focused on innovative disruption
Entrepreneurial outlook and independent thinking
Collaboration and opportunities to develop innovative solutions
Growth opportunities within the organization