Lead Data Engineering Services

Summary

Join our team as a Lead-Level Data Engineering Contractor based in Mexico or Argentina! Collaborate with app developers and data stakeholders to implement data system changes and address data inquiries. Lead initiatives, from problem definition to planning, using epics and blueprints. Leverage your expertise to create documentation, presentations, and conduct reviews. Build and maintain data pipelines and DAG tooling, and establish a comprehensive data catalog. This role requires advanced skills in SQL, Python, and data pipeline management.

Requirements

• Mastered proficiency in SQL, Python, and relational datastores (columnar and row databases)
• Proficiency in building and maintaining data pipelines and DAG tooling (Dagster, Airflow, etc)
• Advanced experience with event-based pipelines and CDC tooling
• Advanced experience in managing large-scale data migrations in relational datastores
• Advanced experience in optimizing SQL query performance
• Advanced experience with data testing strategies to ensure resulting datastores are aligned with expected business logic
• Experience with DBT orchestration and best practices
• Experience with enabling monitoring, health checks and alerting on data systems and pipelines
• Experience establishing and maintaining a data catalog with business-related metadata
• Experience building tools and automation to run data infrastructure

Responsibilities

• Work alongside app developers and data stakeholders to create data system changes and to respond to data inquires
• Lead initiatives and problem definition scoping, design, and planning through epics and blueprints
• Develop documentation, technical presentation, discussion, and incident reviews
• Build and maintain data pipelines and DAG tooling
• Establish and maintain a data catalog with business-related metadata

Preferred Qualifications

• Experience with writing and maintaining cloud-based infrastructure for data pipelines (AWS, GCP and Terraform)
• Experience in document, graph or schema-less datastores