Senior Data Engineer: Snowflake + dbt Platform (Remote)

Jump Inc.; Northern (KY); Hybrid; USD 190,000 - 210,000; Full time

Benefits offered by this job

Remote first

Competitive salary and equity

Flex PTO policy

401(k)

Generous medical, dental and vision

16 weeks paid parental leave

$1,000 reimbursement for work-fromHome

$1,000 reimbursement for learning and,

Job summary

Jump is seeking a Senior Data Engineer to own the data platform, focusing on reliability and performance of a Snowflake/dbt stack. You will build and maintain pipelines, tests, and governance to deliver trustworthy data for internal dashboards and client products.

You will design scalable data architectures, implement monitoring, and contribute to AI/ML data initiatives while embracing a hands-on, high-ownership role.

Qualifications

• 6+ years of data engineering experience.
• Own complex data systems from design to production.
• Production-grade SQL and Snowflake expertise.
• Deep dbt knowledge for testing and deployment.

Responsibilities

• Build and maintain ELT pipelines in Snowflake with dbt.
• Design data orchestration and workflows as the platform grows.
• Write dbt tests to catch issues early.
• Document models and data sources for discoverability.
• Build monitoring and alerting for pipeline failures.
• Optimize Snowflake design and materialization for cost/perf.
• Implement access controls and governance aligned with standards.
• Support AI/ML data needs with reliable data access.
• Apply Git-based version control and CI/CD practices.

Skills

Data engineering

System design

Stakeholder management

SQL proficiency

Python

Data pipelines

Testing/monitoring

Tools

Snowflake

dbt

Git/CI-CD

Python

Job description

Jump is seeking a Senior Data Engineer to own the data platform, focusing on reliability and performance of a Snowflake/dbt stack. You will build and maintain pipelines, tests, and governance to deliver trustworthy data for internal dashboards and client products.

You will design scalable data architectures, implement monitoring, and contribute to AI/ML data initiatives while embracing a hands-on, high-ownership role.