Staff Data Engineer: Lead Data Platforms & Impact

Jobber; United States; Remote; USD 121,000 - 164,000; Full time

Benefits offered by this job

Extended health benefits

Stock options

Career development

Job summary

Jobber is seeking a Staff Data Engineer to lead our Data Integration team. You will design and maintain scalable batch and streaming pipelines, mentor engineers, and help shape the data platform that powers product decisions and business growth.

You’ll own reliability, governance, and self-serve access, collaborating with analytics, product, and engineering to unlock insights. This is a hands-on, leadership-heavy role balancing coding, architecture, and strategy.

Qualifications

• Hands-on experience with batch and real-time data processing frameworks.
• Ability to design scalable data architectures across data lake/warehouse layers.
• Strong knowledge of AWS data services and best practices.
• Demonstrated technical leadership and ability to guide engineers.
• Experience with reliability, observability, and DevOps practices.
• Excellent collaboration and communication in cross-functional teams.

Responsibilities

• Shape foundational data components with scalable batch and real-time pipelines.
• Demonstrate technical mastery and mentor team members across levels.
• Drive reliability with SLAs, RTO/RPO, and disaster recovery planning.
• Advance observability, governance, and data lineage across platforms.
• Develop self-service data access tools to empower analytics and data science.
• Align data engineering priorities with strategic roadmaps through partnerships.

Skills

Batch processing

Real-time processing

AWS cloud

Data modeling

CI/CD

Tools

Terraform

CloudFormation

Airflow

Snowflake

Kubernetes

Job description

Jobber is seeking a Staff Data Engineer to lead our Data Integration team. You will design and maintain scalable batch and streaming pipelines, mentor engineers, and help shape the data platform that powers product decisions and business growth.

You’ll own reliability, governance, and self-serve access, collaborating with analytics, product, and engineering to unlock insights. This is a hands-on, leadership-heavy role balancing coding, architecture, and strategy.