📋 Description

• Design, build, and own custom data pipelines that integrate source systems with the data warehouse
• Develop and operate Airflow DAGs for scheduled and event-driven workflows, ensuring reliable and
• Build dbt models and governed semantic layers that provide trusted data for analysts, internal
• Create reusable patterns for incremental synchronization, retries, replay, backfills, and event
• Implement monitoring, data-quality checks, reconciliation, alerting, and logging to identify issues
• Diagnose and resolve production incidents involving missing, delayed, duplicated, or inaccurate

🎯 Requirements

• 3+ years of experience in data engineering, analytics engineering, or a closely related engineering
• Strong production-level Python and advanced SQL skills, with an emphasis on clean, maintainable
• Hands-on experience designing, building, and operating Airflow workflows for custom data pipelines.
• Strong knowledge of dbt and dimensional modeling, including grain, keys, facts, dimensions
• Experience developing custom integrations using third-party APIs, webhooks, files, or event streams
• Deep understanding of API ingestion, including authentication, pagination, rate limits, incremental

🎁 Benefits

• Competitive base salary of $150,000–$170,000, plus a bonus, depending on experience and location.
• Comprehensive benefits package designed to support employee and family well-being.
• Strong healthcare and benefits coverage.
• Generous paid time off.
• Wellness-focused perks and access to company products.
• Fully remote, high-trust working environment.