Senior Data Engineer

We are seeking a Senior Data Engineer to build and maintain secure, reliable, and scalable data pipelines, warehouse models, and analytical datasets supporting people insights. This role combines hands-on data engineering with data modeling, platform reliability, semantic-layer design, and governed access for both business intelligence tools and AI-enabled interfaces. Enterprise experience strongly preferred. Key Responsibilities - Develop and maintain secure, efficient data pipelines using dbt, PySpark, and Python applications. - Build extraction, transformation, and loading infrastructure using Python, dbt, Terraform, AWS Glue, Amazon EMR, and Amazon S3. - Integrate data from APIs, cloud systems, Google Sheets, and other structured sources. - Create and maintain Snowflake warehouse models, datamarts, and analytics-ready datasets. - Develop automated data-quality tests and improve internal data-engineering processes. - Monitor production pipelines and help maintain a 99.5% uptime objective. - Design semantic views, ontology layers, business-friendly entities, relationships, and certified metrics over warehouse models. - Build governed natural-language data experiences using Snowflake Cortex Analyst, Cortex Search, or equivalent LLM-native query layers. - Configure secure Model Context Protocol connections or comparable interfaces between governed data sources and internal AI tooling. - Document data models, pipelines, business logic, operational procedures, and technical decisions comprehensively. Must-Have Skills - 5+ years of relevant experience. - Hands-on Snowflake experience, including data modeling, datamarts, and data warehouse design. - Hands-on dbt experience for data transformations. - Strong Python experience, including object-oriented programming and data scripting. - Hands-on Airflow experience for pipeline orchestration. - Experience integrating REST APIs and ingesting data from external sources. - Hands-on Google BigQuery querying and optimization experience. - Experience securely handling sensitive data at large scale. - Experience with real-time or near-real-time data processing from APIs, Google Sheets, or comparable sources. - Strong SQL skills, including highly optimized queries. - Comprehensive technical documentation skills. - Advanced English communication skills. Nice-to-Have Skills - Experience designing semantic layers or semantic models that provide business-object abstraction over dbt and warehouse models. - Experience with Snowflake Cortex Analyst, Cortex Search, or an equivalent LLM-native query layer. - Experience with Model Context Protocol or a similar tool-calling and context-exposure framework. - Familiarity with prompt and context engineering for grounding AI agents in certified data sources. Required Tools & Platforms - Snowflake. - dbt. - Python and PySpark. - Apache Airflow. - Google BigQuery. - SQL. - REST APIs. - Terraform. - AWS Glue, Amazon EMR, and Amazon S3. Location, Time & Engagement - Candidates must be based in LATAM. - Full US Central Time coverage is required. - This is a contract engagement at 40 hours per week. - The anticipated engagement runs through March 31, 2027. - This is not currently a contract-to-hire opportunity.