Data Engineer

Build and maintain scalable, reliable data pipelines and analytics-ready models. This is a hands-on, customer-facing role requiring strong problem-solving, ownership, and the ability to work independently with US-based customers. Key Responsibilities: - Build ELT pipelines using BigQuery OR Snowflake, dbt, and cloud services - Write production-grade Python code for ingestion, transformation, and automation - Design analytics-ready data models - Work directly with customers to gather and clarify requirements - Ensure data quality via testing, validation, and monitoring - Debug pipeline failures, data issues, and performance bottlenecks - Participate in code reviews and follow engineering best practices - Work with 3–5 hours overlap with US EST/CST/PST. What Success Looks Like: - Reliable pipelines with minimal production issues - Clear communication with customers and stakeholders - Well-tested, maintainable SQL and Python code.

To be a hands-on, customer-facing role requiring strong problem-solving, ownership, and the ability to work independently with US-based customers. Requires 2–4 years of data engineering or analytics engineering experience. Strong SQL (joins, CTEs, window functions) skills are required, along with hands-on BigQuery OR Snowflake experience. Strong Python coding used in production pipelines and prior customer-facing or stakeholder-facing experience are also needed.