Data Engineer - GCP

About the Company We are a dynamic team focused on building innovative and scalable data solutions on Google Cloud Platform (GCP). About the Role Our Google Cloud Data Engineer will play a key role in designing, developing, and managing scalable data pipelines and data infrastructure, ensuring data availability, accuracy, and performance for business insights and machine learning models. Responsibilities Data Pipeline Development and Management : Design, build, and maintain scalable and reliable data pipelines using Cloud Dataflow, Cloud Pub/Sub, and Cloud Composer. Develop ETL/ELT processes to process and transform large volumes of structured and unstructured data. Optimize data pipeline performance, scalability, and reliability. Ensure data processing and ingestion workflows are monitored and meet performance SLAs. Data Storage and Management : Design and implement data storage solutions using BigQuery, Cloud Storage, and Firestore. Optimize data structures and partitioning for performance and cost efficiency. Ensure data security, integrity, and availability in all storage solutions. Manage data lifecycle policies and archiving processes. Data Transformation and Processing : Develop data transformation processes using BigQuery, Apache Beam, and Cloud Functions. Implement data quality checks, validation rules, and monitoring solutions. Support real-time and batch data processing needs. Data Integration and Automation : Integrate data from multiple sources, including APIs, databases, and third‑party applications. Automate data ingestion, transformation, and export using tools like Cloud Composer and Cloud Functions. Ensure data consistency across different environments and systems. Collaboration and Stakeholder Engagement : Work closely with data scientists and analysts to understand data needs and business goals. Provide technical guidance and best practices to the data engineering and business teams. Collaborate with security and compliance teams to ensure data governance standards are met. Performance Monitoring and Troubleshooting : Monitor data pipeline performance and troubleshoot issues in real‑time. Analyze data pipeline failures and implement fixes to prevent recurrence. Set up logging and monitoring using Stackdriver and Cloud Monitoring. Qualifications Bachelor’s degree in Computer Science, Data Engineering, or a related field; Master’s degree is a plus. 3+ years of experience in data engineering, with at least 2+ years working with Google Cloud Platform. Google Professional Data Engineer certification is required. Strong proficiency with GCP services such as BigQuery, Cloud Dataflow, Cloud Composer, Cloud Pub/Sub, Firestore, and Cloud Functions. Hands‑on experience with big data tools and frameworks such as Apache Beam, Hadoop, Spark, or Flink. Hands‑on experience with dbt. Proficiency in programming languages such as Python, Java, or Scala. Strong knowledge of SQL, data modeling, and query optimization. Experience with CI/CD tools and version control (e.g., Git, Cloud Build). Strong understanding of data governance, security, and compliance requirements. Ability to manage large‑scale data processing and real‑time data pipelines. Excellent problem‑solving, analytical, and communication skills. Must be a U.S. Citizen or Green Card holder. Preferred Skills Experience with machine learning pipelines and AI/ML model deployment. Familiarity with Terraform and Infrastructure as Code (IaC) principles. Experience with NoSQL databases and key‑value stores on GCP. Knowledge of containerization and orchestration using Google Kubernetes Engine (GKE). Compensation and Benefits Competitive salary and performance‑based incentives. Comprehensive health, dental, and vision coverage. Professional development and training opportunities (including GCP certification). Flexible work environment and remote work options. Equal Opportunity Statement Candidates must be U.S. Citizens or Green Card holders. #J-18808-Ljbffr The Data Sherpas