Principal Data Engineer

• Lead the technical direction for how data flows, scales, and powers decisions at JobGet
• Own the data architecture behind the 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, and operational readiness standards for tier-1 pipelines
• Design and implement robust batch data pipelines using Snowflake and dbt
• Establish data modeling standards for analytics, ML feature engineering, and product instrumentation
• Resolve complex data integration, performance, and reliability challenges through hands-on implementation
• Architect and evolve streaming infrastructure using KSQL and Apache Flink
• Partner with Platform Engineers and Data Analysts to design feature stores, training data pipelines, and inference-ready datasets
• Ensure data products are well-modeled, documented, and performant for self-serve analytics
• Define and enforce data governance standards for quality, lineage, access control, and cataloging
• Implement data validation frameworks, SLA monitoring, and anomaly detection
• Design data systems with privacy-by-default principles aligned with CCPA and GDPR
• Mentor and level up data engineers through code reviews and design guidance
• Collaborate with Software Engineering, Product, and Analytics on data requirements
• Drive adoption of data platform standards and architectural patterns across teams
• Identify and fix bottlenecks, architectural bugs, and performance issues impacting system stability

• 10+ years of data engineering experience
• At least 3–5 years operating at a principal or staff IC 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 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 that directly supports 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
• Strong grasp of data governance fundamentals, including data lineage, cataloging, access control, and quality monitoring
• Familiarity with real-time and near-real-time data architectures, including streaming, event-driven design, and CDC
• Exceptional communication and stakeholder management skills
• Must be currently located and legally approved to work in Mexico

• Savings Fund (Fondo de Ahorro)
• Bonus
• 30 Day El Aguinaldo
• 20 Days of PTO
• Remote-first
• Flexible work hours - our employees are in multiple time zones
• Medical coverage
• Parental leave