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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Google Cloud Platform Data Engineer - **Company:** Everforth Apex - **Location:** United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Application Frameworks, Big Data, BigQuery, Cloud Computing, Cloud Database, Information Systems, Computer Programming, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Dataspaces, Data Systems, Data Warehousing, Relational Databases, Github, Python (Programming Language), Machine Learning, Cloud Services, Tensorflow, Data Streaming, Unstructured Data, Enterprise Data Management, Data Processing, Google Cloud, Data Lakes, Scikit Learn, Information Technology, Data Management, Data Lakehouse, Software Version Control, Data Pipelines - **Published:** August 14, 2026 - **Apply:** https://www.dice.com/job-detail/5d0ee278-4e51-4657-bb7d-9e41986c535e ## About the Role Data Engineering & Cloud Platforms * 5+ years of professional experience in Data Engineering. * Hands-on experience designing, developing, and maintaining modern data architectures and data platforms. * Strong experience with Google Cloud Platform (Google Cloud Platform) services and cloud-native data solutions. * Advanced knowledge of BigQuery for data warehousing, analytics, and large-scale data processing. Programming & Automation * Strong proficiency in Python for data engineering, automation, and data pipeline development. * Experience developing reusable frameworks, scripts, and automation solutions. * Proficiency using GitHub and modern source control practices. Data Architecture & Modeling * Experience designing and implementing: + Data Warehouses + Data Lakes + Lakehouse Architectures * Strong understanding of data modeling concepts and relational database design. * Experience building scalable ETL/ELT pipelines and data integration solutions. Analytics & Machine Learning Enablement * Experience supporting machine learning and advanced analytics workloads through scalable data solutions. * Ability to work with large, complex datasets to support business intelligence and predictive analytics initiatives., * Experience with machine learning frameworks such as: + TensorFlow + Scikit-learn * Understanding of algorithms and statistical modeling techniques. * Experience supporting data science and AI/ML initiatives. * Exposure to real-time or streaming data architectures. * Experience implementing enterprise-scale data governance and data quality solutions., * Google Cloud Platform (Google Cloud Platform) * BigQuery * Python * GitHub * Data Engineering * ETL/ELT Development * Data Pipelines * Data Warehousing * Data Lakes * Data Modeling * Machine Learning Enablement Preferred Skills * TensorFlow * Scikit-learn * Algorithms * Relational Databases * Advanced Data Modeling * Data Lakehouse Architecture Education Required * Master's Degree in Computer Science, Data Science, Engineering, Information Systems, or a related technical field Preferred * Advanced certifications in Cloud, Data Engineering, Analytics, or Machine Learning ## Description The Data Engineer is responsible for designing, building, and maintaining scalable data solutions that support enterprise analytics, machine learning, and business intelligence initiatives. This role develops and optimizes data infrastructure, pipelines, and platforms that enable the efficient collection, storage, processing, and analysis of large volumes of structured and unstructured data. The ideal candidate will possess strong expertise in cloud-based data engineering, data modeling, pipeline development, and modern data platforms, while partnering closely with business and technology stakeholders to deliver reliable, high-performing data solutions., * Collaborate with business and technology stakeholders to understand current and future data requirements and translate them into scalable technical solutions. * Design, develop, and maintain reliable, efficient, and scalable data infrastructure supporting data collection, storage, transformation, and analytics. * Build and optimize end-to-end data pipelines, workflows, and data models to ensure accurate and efficient data processing. * Design, implement, and support enterprise data platforms, including data warehouses, data lakes, and lakehouse architectures. * Develop tools, frameworks, scripts, and automation capabilities that improve data engineering efficiency and reduce manual effort. * Create and maintain robust data integration solutions across multiple systems and sources. * Ensure data quality, performance, reliability, and scalability through monitoring, testing, and continuous optimization. * Partner with data scientists, analysts, and application teams to support advanced analytics and machine learning initiatives. * Identify opportunities to improve data architecture, pipeline performance, cost optimization, and operational efficiency. * Implement data governance, security, and best practices across the data ecosystem. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [The Cloud is Calling: Answer with In-Demand Skills](https://www.wearedevelopers.com/videos/945-the-cloud-is-calling-answer-with-in-demand-skills) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Making Data Warehouses fast. A developer's story.](https://www.wearedevelopers.com/videos/302-making-data-warehouses-fast-a-developer-s-story) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) ## Related Articles - [Got AI ideas but no money? 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