
51 - 200 employees
Founded 2019
🎯 Recruiter
🏪 Marketplace
👥 HR Tech
Recruitment • Marketplace • HR Tech
JobGet is the go-to marketplace and social job network for the Everyday Worker. It’s a fast-growing app that connects service-industry job seekers (restaurants, food service, retail, hospitality, healthcare, warehouse, trucking, customer support, and more) with employers using skill-based matching to surface local, high-intent candidates. JobGet simplifies and speeds hiring by learning about job seekers and expanding employer candidate pools beyond traditional job sites.
🔥 1 minute ago
Where this job comes from
Posted on JobGet's careers page, not through a job board
First seen by Remote Rocketship 1 minute ago

51 - 200 employees
Founded 2019
🎯 Recruiter
🏪 Marketplace
👥 HR Tech
Recruitment • Marketplace • HR Tech
JobGet is the go-to marketplace and social job network for the Everyday Worker. It’s a fast-growing app that connects service-industry job seekers (restaurants, food service, retail, hospitality, healthcare, warehouse, trucking, customer support, and more) with employers using skill-based matching to surface local, high-intent candidates. JobGet simplifies and speeds hiring by learning about job seekers and expanding employer candidate pools beyond traditional job sites.
• Lead the technical direction for how data flows, scales, and powers decisions at JobGet • Own the data architecture behind JobGet’s platform connecting job seekers with employers • Lead design reviews for critical platform components and evaluate scalability, cost, reliability, and time-to-insight trade-offs • Evaluate and introduce modern data stack tooling such as Databricks, Snowflake, dbt, and Kafka • Own observability, alerting, runbooks, failover strategies, and reprocessing protocols for tier-1 pipelines • Make significant technical decisions and drive projects end-to-end with limited oversight • Design and implement batch data pipelines using Snowflake and dbt • Establish data modeling standards including schema design, dimensional modeling, and data contracts • Resolve complex data integration, performance, and reliability challenges through hands-on implementation • Architect and evolve streaming infrastructure using KSQL and Apache Flink for real-time matching, recommendations, and product decisioning • Partner with Platform Engineers and Data Analysts to design feature stores, training data pipelines, and inference-ready datasets • Improve analytics delivery through well-modeled, documented, and performant data products • Evaluate and integrate AI-powered tools for operational efficiency and developer productivity • Define and enforce data governance standards for quality, lineage, access control, and cataloging • Implement validation frameworks, SLA monitoring, and anomaly detection • Design privacy-by-default data systems aligned with CCPA, GDPR, and applicable regulations • Mentor and develop data engineers through code reviews and design guidance • Collaborate with Software Engineering, Product, and Analytics teams • Drive adoption of data platform standards and architectural patterns across teams • Identify and fix bottlenecks, architectural bugs, and performance issues affecting system stability
• 10+ years of data engineering experience • At least 3–5 years operating at a principal or staff individual-contributor level in a start-up environment • Production-grade experience with Snowflake and dbt (required) • Experience with real-time streaming technologies such as KSQL or Apache Flink is strongly preferred • Hands-on AWS experience at scale, including cloud data architecture, cost governance, and infrastructure-as-code • Terraform experience is a nice-to-have • DataOps experience, including CI/CD for data pipelines, automated testing frameworks, and production deployment practices • Significant, demonstrated AI usage in day-to-day engineering work is required • Expert-level proficiency in Python and SQL • Strong command of distributed systems, data pipeline design, and performance optimization • Strong data modeling background, including dimensional modeling, schema design, and data contracts • Experience building data infrastructure supporting ML/AI systems, including feature pipelines, training data management, and inference-layer data serving • Demonstrated track record of setting technical standards across teams through RFCs, architecture reviews, or platform migrations • Practical experience implementing data lineage, cataloging, access control, and quality monitoring in production • Familiarity with real-time and near-real-time data architectures, including streaming, event-driven design, and CDC • Exceptional communication and stakeholder management skills • Builder’s mentality and operator’s discipline • Ability to work in the United States; application asks for citizenship or employment eligibility and state of residence
• Purpose-driven organization • Flexible time off • Remote-first work arrangement • Flexible work hours across multiple time zones • Medical and dental plans • Parental leave • Employee stock options
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