Cloud Data Engineer: Pipelines, BigQuery & Airflow

Empower BI; United States; Remote; USD 120,000 - 170,000; Full time

Job summary

Empower BI is seeking a data engineer to build and maintain data platforms that support operational reporting, supply-chain processes, and forecasting across multiple markets. You will blend hands-on pipeline development with data architecture and platform modernization in a cloud environment.

Work with analysts and data scientists to translate business needs into robust data solutions, own data quality and reliability, and help drive long-term stability of the data ecosystem while collaborating

Qualifications

• Strong practical experience with BigQuery, Airflow, and Python.
• Good understanding of Google Cloud data services.
• Strong SQL and data-modelling fundamentals.
• Basic DevOps knowledge, including Kubernetes, service accounts, and CI/CD fundamentals.
• Able to work independently and deliver reliably across both development and maintenance.
• Comfortable collaborating in a distributed, multicultural environment.

Responsibilities

• Build and optimize data pipelines and models in BigQuery.
• Create, maintain, and automate Airflow workflows.
• Develop scalable data workflows in Python.
• Enhance and operate a large Google Cloud data environment.
• Partner with analysts and data scientists to turn business needs into robust data solutions.
• Own data quality, reliability, and operational continuity while contributing to platform evolution.

Skills

BigQuery

Airflow

Python

SQL

Data modelling

Google Cloud

Tools

Kubernetes

CI/CD

Job description

Empower BI is seeking a data engineer to build and maintain data platforms that support operational reporting, supply-chain processes, and forecasting across multiple markets. You will blend hands-on pipeline development with data architecture and platform modernization in a cloud environment.

Work with analysts and data scientists to translate business needs into robust data solutions, own data quality and reliability, and help drive long-term stability of the data ecosystem while collaborating