Data Engineer

The Opportunity

The Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and data assets that support data-driven decision making across the organization. Working closely with cross-functional data teams, they integrate new data sources into existing data products while leveraging GCP technologies to manage and process large-scale datasets. The role focuses on developing reusable, configurable, and efficient data pipeline frameworks, as well as producing clean, modular, and well-documented code that enhances collaboration, reduces operational overhead, and accelerates future development.

What to Expect

• Data Ingestion and Processing: Design and implement robust data pipelines to collect, clean, transform, and store large volumes of data using GCP services like BigQuery and Cloud Storage, as well as DataBricks 
• Data Warehousing and Analytics: Build and optimize data warehouses on Google BigQuery for efficient data analysis and reporting.
• Data Modeling: Design and implement scalable data models to support strategic data products, business intelligence, and machine learning applications. 
• ETL/ELT Development: Develop and maintain Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) processes using GCP tools.
• Performance Optimization: Continuously monitor and optimize data pipelines and queries for performance and cost-effectiveness.
• Collaboration: Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver data solutions.
   

What you Bring:

• Google Cloud Platform (GCP): Strong proficiency in GCP data services, including BigQuery, Cloud Storage, and DataBricks. Experience with Dataflow is an asset.
• Bachelor's or Master's degree in Math, Computer Science, Software Engineering, or a related field.
• Minimum 3-5+ years of experience in a hands-on data engineering role, with a focus on pipeline development and data modeling on Google Cloud Platform.
• Experience with large-scale data processing and distributed systems.
• Google Cloud Professional Data Engineer Certification or equivalent is a strong asset for this role.
• Strong data engineering expertise, building and orchestrating scalable data pipelines using Airflow, Cloud Composer, Apache Beam, and Python. 
• Advanced SQL and data modeling skills, including complex query development, optimization, schema design, and data analysis. 
• Proven ability to develop dynamic Airflow DAGs and robust data solutions that support efficient, reliable data processing.
• Solid understanding of Agentic AI 

Salary Range: $92,000-$142,000