Senior Data Engineer

New

Nimble GravityFinancial technology

Location: LATAM (Remote), US (Remote)Full-TimeSenior

Salary not disclosed

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Job Details

Have 5–7 years of dedicated data engineering experience.
Have a proven track record building production-grade data pipelines.
Bring advanced, hands-on experience with Snowflake architecture, performance tuning, and data sharing.
Have experience moving data across hybrid on-premises and cloud environments.
Have experience with batch, streaming, and event-driven data integration patterns.
Have experience building or maintaining semantic layers, such as dbt Semantic Layer or Snowflake Cortex/Semantic definitions.
Have experience structuring data for downstream AI, LLM, or natural-language search features.
Have strong Python skills, particularly in cloud environments, and strong SQL capabilities.
Have exposure to dbt; this is highly preferred.
Azure data tools experience, including Azure Data Factory, is a strong plus; familiarity with AWS data ecosystems is nice to have.
Bring a collaborative, coaching mindset and an interest in teaching and establishing governance.

Design, build, and maintain scalable batch, real-time streaming, and event-driven data pipelines from on-premises and cloud sources.
Own development of the Snowflake data platform, including performance, modeling, and storage structures.
Build transformation pipelines that deliver high-quality data to Snowflake and dbt AI features.
Design and maintain semantic layers and metadata models for natural-language interfaces.
Establish reference architectures, templates, and CI/CD best practices for decentralized line-of-business teams.
Manage and provide career mentorship to one data engineer.
Guide domain data analysts in improving their engineering practices.
Drive adoption of dbt and explore AWS and Azure data tools to optimize data flow.

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