Data Engineer (GCP, BigQuery) in Abbeyville, Colorado at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer (GCP, BigQuery) based in United States.

This role offers the opportunity to design and build scalable data solutions that support business intelligence, analytics, and AI-driven initiatives.
You will work at the intersection of cloud data engineering, data architecture, and advanced analytics to improve how teams access and use critical information.
The position involves building reliable data pipelines, optimizing large-scale datasets, and ensuring high standards of performance, security, and data quality.
You will collaborate closely with data scientists, software engineers, architects, and business stakeholders in a highly collaborative environment.
This is an opportunity to influence modern data infrastructure while solving complex challenges through cloud technologies and automation.
The role is ideal for a data-focused engineer who enjoys innovation, continuous improvement, and creating meaningful business impact through technology.

As a Data Engineer, you will develop and maintain cloud-based data solutions that enable advanced reporting, analytics, and AI initiatives. You will contribute to data architecture improvements, ensure data reliability, and collaborate with cross-functional teams to deliver scalable solutions aligned with business needs.

• Develop BigQuery procedures, functions, and database objects using advanced BigQuery SQL and ANSI SQL expertise.
• Build and optimize scalable data models within cloud data platforms, with a focus on BigQuery-based architectures.
• Manage data storage strategies, including partitioning and clustering, to improve performance and reliability.
• Develop and enhance cloud-based data warehouse solutions using modern data engineering practices.
• Collaborate with data scientists, software engineers, architects, and business teams to understand requirements and deliver effective solutions.
• Implement data validation processes, error handling, and quality controls to maintain accurate and reliable datasets.
• Improve the full data lifecycle, including ingestion, ETL processes, transformation layers, and reporting solutions.
• Create technical documentation to support architecture discussions, implementation decisions, and team knowledge sharing.
• Stay current with emerging trends in data engineering, cloud technologies, and big data solutions.

The ideal candidate has strong experience designing and maintaining cloud-based data solutions, with expertise in SQL, Python, and modern data warehouse technologies. You should be analytical, detail-oriented, and comfortable collaborating across technical and business teams.

• 3+ years of experience building, modeling, and maintaining data solutions in cloud environments.
• Strong proficiency in SQL and Python for manipulating, managing, storing, and retrieving data assets.
• Hands-on experience with Google BigQuery and cloud-based data warehousing solutions.
• Experience with cloud data platforms such as Google Cloud Platform, Snowflake, Amazon Redshift, Microsoft Azure Synapse Analytics, or Databricks Lakehouse.
• Knowledge of BigQuery optimization techniques and cloud data service management.
• Experience with Agile methodologies, preferably Scrum, and tools such as Jira and Confluence.
• Strong analytical thinking, problem-solving abilities, and attention to detail.
• Bachelor’s degree in Computer Science, Management Information Systems, Computer Information Systems, or equivalent practical experience.
• Ability to work collaboratively while taking ownership of technical solutions and continuous improvements.

• Competitive annual compensation range aligned with experience, skills, and responsibilities.
• Remote work flexibility.
• Medical, dental, and vision coverage.
• Paid holiday and vacation time.
• Health and wellness days.
• Additional birthday bonus day.
• Opportunity to work on impactful cloud data and AI initiatives.
• Supportive culture focused on collaboration, inclusion, learning, and professional growth.
• Opportunity to work with modern data technologies and contribute to innovative solutions at scale.