Lead Data Engineer: BigQuery, Snowflake & ETL Pipelines

BarkleyOKRP; United States; A distancia; USD 90.000 - 135.000; Jornada completa

Descripción de la vacante

BarkleyOKRP is seeking a Data Engineer to maintain, clean, and manipulate data across operational and analytics databases. You will collaborate with data scientists, analytics teams, reporting teams, and IT to implement database requirements, analyze performance, and troubleshoot issues.

You will design, develop, and optimize data pipelines, integrate data from suppliers, validate deliveries, and ensure scalable data architectures using BigQuery, Snowflake, and AWS in a dynamic environment.

Formación

• Bachelor’s degree in CS/IT or equivalent.
• 3–4+ years of SQL on large-scale datasets.
• Cloud data engineering experience with Snowflake preferred.
• Experience with Python and ETL development lifecycle.
• Knowledge of BigQuery, GCP services, and data warehousing.

Responsabilidades

• Design, develop, and maintain BigQuery data warehouse solutions.
• Build data pipelines and ETL processes for analytics.
• Collaborate with data suppliers and cross-functional teams.
• Validate data delivery and resolve data issues.
• Document operational processes and improve data delivery.
• Stay current with Snowflake and AWS best practices.
• Provide training on Snowflake best practices.
• Improve infrastructure for scalability and automation.

Conocimientos

SQL on large datasets

Python

Data warehousing

ETL design

Data pipelines

Cloud data engineering

Communication

Educación

Bachelor’s degree in Computer Science or Information Technology

Herramientas

BigQuery

Snowflake

AWS

GCP

ETL tooling

Descripción del empleo

BarkleyOKRP is seeking a Data Engineer to maintain, clean, and manipulate data across operational and analytics databases. You will collaborate with data scientists, analytics teams, reporting teams, and IT to implement database requirements, analyze performance, and troubleshoot issues.

You will design, develop, and optimize data pipelines, integrate data from suppliers, validate deliveries, and ensure scalable data architectures using BigQuery, Snowflake, and AWS in a dynamic environment.