Data Engineer - SQL / Snowflake
Zoolatech
Team builds and runs the core Marketplace analytics data products and platform (Snowflake/dbt/Dagster, pipelines, models, observability) that other teams rely on for hiring, performance, and marketplace insights.
Resource will provide technical execution and analytics leadership in support of the ADP Engineering team’s (part of the Central Analytics Organization) workstreams within the Marketplace domain and related initiatives. Develop and Optimize Data Pipelines: Build scalable pipelines using Python and dbt to support efficient data transformation and integration. Data Management and Modeling: Design and maintain database tables, Snowflake structures, and data models to support reporting and analytics needs. ETL Processes: Develop robust ETL/ELT workflows for extracting, transforming, and loading data while maintaining data quality and consistency. Data Monitoring and Observability: Improve pipeline reliability through monitoring, observability, and proactive issue resolution. Reporting and Dashboards: Build dashboards and provide updates that support actionable insights and business decision-making. Collaborate and Communicate: Partner cross‑functionally to align on requirements, communicate progress, and ensure transparency across initiatives.
Must‑Have Skills:
- 7+ years with SQL – Strong ability to query, transform, validate, and optimize data for analytics, reporting, and pipeline workflows.
- 5-7+ years with Python – Experience building scalable data pipelines, automation scripts, and data processing workflows.
- 5-7+ years with Snowflake – Hands‑on experience designing and maintaining cloud data warehouse structures, tables, and performant data models.
- DBT – Experience developing modular data transformations, testing, and documentation within modern ELT workflows.
- AWS – Familiarity with AWS cloud services supporting scalable data storage, processing, and pipeline orchestration.
- ETL/ELT – Experience building reliable workflows for extracting, transforming, loading, and validating data from multiple sources.
- Data Observability – Ability to monitor pipeline health, troubleshoot workflow issues, and proactively improve reliability and data quality.
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Vacante publicada el 1 día atrás
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