Data Engineer, Senior to Staff Level

Sanity.io

Data Engineer responsible for architecting and maintaining the data ecosystem at Sanity.io. Collaborating across teams to enhance data accessibility and reliability.

Posted 7/15/2026full-timeSan Francisco • California • 🇺🇸 United StatesSenior💰 $180,000 - $240,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in architecting and maintaining data ecosystems, including data pipelines and warehouses, with a strong focus on data quality, security, and compliance. Proficient in SQL, Python, and various data orchestration tools to optimize performance and manage strategic projects.

Highest-signal resume keywords

Data Warehouse ArchitectureSQL ExpertisePython ProgrammingWorkflow Orchestration (e.g. Dagster, Airflow)Google Cloud Platform (GCP)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline InfrastructureData Quality MonitoringELT/Event Tooling (e.g. Airbyte, RudderStack)Google DatastreamBigQueryInfrastructure as Code (IaC)TerraformMonitoring and AlertingData Security and IntegrityRegulatory Compliance

Soft Skills

Strong Organization SkillsAnalytical AcumenSelf-MotivatedExcellent Communication Skills

Tools & Technologies

DbtGoogle Cloud PlatformTerraformDagsterAirflowAirbyteRudderStackGoogle DatastreamBigQuery

Industry Keywords

Data EcosystemData TelemetryPipeline HealthSLA/SLO ImplementationCI/CD Practices

Tech Stack

Tools & technologies

AirflowBigQueryCloudGoogle Cloud PlatformPythonSQLTerraform

About the role

Key responsibilities & impact

Architect, build, and maintain Sanity's data ecosystem: pipelines, integrations, and the warehouse
Partner with engineering teams to implement and scale product telemetry across our product surfaces
Work closely with analysts, engineers, and other stakeholders to understand their data needs
Build and maintain monitoring, alerting, and logging that give clear visibility into pipeline health
Implement SLAs/SLOs for critical pipelines and develop data quality monitoring
Build and maintain the data team's eval framework
Optimize pipeline performance and cost as data volumes grow
Drive platform-wide engineering standards: code quality, testing frameworks, CI/CD practices, schema conventions, and documentation
Create and deploy strategies to maintain data security, integrity, and regulatory compliance

Requirements

What you’ll need

5+ years of experience architecting data warehouse and pipeline infrastructure
Strong expertise in SQL and Python
Fluent in dbt, workflow orchestration tools (e.g. Dagster, Airflow)
ELT/event tooling (e.g. Airbyte, RudderStack) in a fast-moving data environment
Demonstrated success building and maintaining large-scale data pipelines using technologies such as Google Datastream and BigQuery
Hands-on with Google Cloud Platform, including IaC tools like Terraform and cloud network infrastructure
Active experience with AI-assisted development tools integrated into engineering workflows
Strong organization skills to effectively manage and lead strategic projects
Comfortable with ambiguity, strong analytical acumen, self-motivated
Excellent communication skills, able to work across dynamic teams and explain ideas to technical and non-technical audiences

Benefits

Comp & perks

A highly-skilled, inspiring, and supportive team
Positive, flexible, and trust-based work environment that encourages long-term professional and personal growth
A global, multi-culturally diverse group of colleagues and customers
Comprehensive health plans and perks
A healthy work-life balance that accommodates individual and family needs