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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:** Experienced - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Business Analytics Applications, Data Analysis, Application Frameworks, Automation of Tests, BigQuery, Cloud Computing, Cloud Database, Cloud Engineering, Information Systems, Databases, Information Engineering, Data Governance, Data Infrastructure, Data Masking, Data Security, Data Systems, Data Warehousing, Relational Databases, Software Design Patterns, DevOps, Data Flow Control, Information Lifecycle Management, Python (Programming Language), PostgreSQL, MySQL, NoSQL, Cloud Services, Cloudera, Service-Oriented Architecture, Software Engineering, SQL Databases, Data Streaming, Unstructured Data, Enterprise Data Management, Google Cloud, Cloud Platform System, Data Ingestion, Infrastructure as Code (IaC), Build Management, Data Lakes, Infrastructure Automation Frameworks, Information Technology, Deployment Automation, Google Cloud Functions, Data Analytics, Data Management, Terraform, Microservices - **Published:** September 30, 2026 - **Apply:** https://www.dice.com/job-detail/00256cdc-6ace-4257-b85f-d55355309280 ## About the Role * Bachelor's Degree in Computer Science, Information Technology, Information Systems, Data Analytics, or a related field (or equivalent combination of education and experience). * 5-7 years of experience in Data Engineering, Software Engineering, or a related technical discipline. * Minimum 2 years of hands-on experience building and deploying cloud-based data platforms, preferably within Google Cloud Platform (Google Cloud Platform). * Strong proficiency in: + SQL + Python + Java * Experience designing and deploying cloud-native data pipelines using: + BigQuery + Dataflow + DataProc + Pub/Sub * Experience with relational databases such as PostgreSQL and MySQL. * Experience working with NoSQL and columnar database technologies, including BigQuery. * Strong understanding of Service-Oriented Architecture (SOA) and microservices. * Familiarity with CI/CD practices and DevOps methodologies. * Experience utilizing Infrastructure as Code (IaC) tools, including Terraform. * Knowledge of data governance frameworks, encryption standards, and data masking techniques. * Strong analytical, troubleshooting, and problem-solving skills. * Experience monitoring and optimizing cloud platform performance, scalability, and cost efficiency. * Passion for innovation, continuous learning, and modern data engineering practices. Preferred Qualifications * Master's Degree in Computer Science, Data Engineering, Analytics, or a related field. * Experience with: + Google Cloud Platform Cloud Functions ## Description We are seeking a highly skilled and experienced Full Stack Data Engineer to play a critical role in the development, enhancement, and support our Enterprise Data Platform. This position is responsible for designing, building, and optimizing scalable cloud-based data solutions within the Google Cloud Platform (Google Cloud Platform) ecosystem. The ideal candidate will possess strong data engineering expertise combined with software development capabilities, enabling them to build end-to-end data solutions that support enterprise analytics, reporting, and business intelligence initiatives. This role will leverage modern cloud-native technologies including BigQuery, Dataflow, Pub/Sub, Cloud Functions, and DataProc while ensuring adherence to data governance, security, scalability, and performance standards., Data Engineering & Platform Development * Partner with business and technology stakeholders to understand current and future data requirements. * Design, develop, and maintain scalable data platforms, pipelines, and infrastructure that support enterprise data initiatives. * Build reliable and efficient data ingestion, transformation, storage, and consumption frameworks for structured and unstructured data. * Design and maintain cloud-based data solutions, including data warehouses, data lakes, and lakehouse architectures. * Develop and optimize data models, pipelines, and workflows to support business intelligence, analytics, and operational reporting. * Create and maintain analytical tools, automation scripts, and reusable frameworks to improve engineering efficiency. * Ensure high data quality, consistency, reliability, and performance across enterprise data assets. * Continuously identify opportunities to improve scalability, cost optimization, and operational efficiency. Cloud & Full Stack Development * Build and deploy cloud-native data solutions utilizing Google Cloud Platform services. * Contribute to end-to-end application and data platform development to enable seamless data flow from source systems through consumption layers. * Develop APIs, services, and integrations supporting enterprise data products and applications. * Implement and support Service-Oriented Architecture (SOA) and microservices-based solutions within cloud environments. Data Governance & Security * Implement and enforce data governance standards, policies, and best practices. * Ensure compliance with data security, privacy, encryption, and masking requirements. * Leverage native Google Cloud Platform security capabilities to protect enterprise data assets. * Manage access controls and data lifecycle governance throughout the platform. Automation & DevOps * Implement Infrastructure as Code (IaC) practices using Terraform and related automation tools. * Support CI/CD pipelines and automated deployment processes. * Utilize workflow orchestration tools such as Astronomer to manage data workflows and scheduling. * Automate operational processes to improve platform reliability, efficiency, and maintainability. Collaboration & Innovation * Collaborate closely with Data Architects, Application Architects, Service Owners, and cross-functional engineering teams. * Drive adoption of cloud data engineering best practices, design patterns, and technical standards. * Evaluate emerging technologies and recommend innovative solutions that enhance platform capabilities. * Foster a culture of continuous improvement, learning, and technical excellence. ## Related Videos - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [MySQL Protocol Features You Should Be Aware Of](https://www.wearedevelopers.com/videos/100267-mysql-protocol-features-you-should-be-aware-of) - [Shifting Stress to Progress— Understanding DevOps to do DevOps Better](https://www.wearedevelopers.com/videos/268-shifting-stress-to-progress-understanding-devops-to-do-devops-better) - [The Cloud is Calling: Answer with In-Demand Skills](https://www.wearedevelopers.com/videos/945-the-cloud-is-calling-answer-with-in-demand-skills) - [Tomorrow's cloud data platforms - fully managed database-as-a-service (DBaaS)](https://www.wearedevelopers.com/videos/254-tomorrow-s-cloud-data-platforms-fully-managed-database-as-a-service-dbaas) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) ## Related Articles - [Got AI ideas but no money? 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