Google Cloud Data Engineer

As a Google Cloud Data Engineer at Mllers Solutions, your primary role will be to enhance data processing capabilities by designing and implementing data pipelines utilizing Google Cloud technologies. You will collaborate with data analysts, business stakeholders, and engineering teams to ensure accurate data processing and availability for analysis and reporting. Key Responsibilities: - Design, develop, and optimize data pipelines using Google Cloud Dataflow, Pub/Sub, and other GCP data services. - Implement data lakes and data warehouses with Google BigQuery for efficient data storage, retrieval, and processing. - Collaborate with data scientists and analysts to understand data requirements and provide business-centric solutions. - Monitor and evaluate data pipeline performance, optimizing and troubleshooting as needed. - Ensure data quality through validation routines and data profiling techniques. - Document data architecture, ETL processes, and operational procedures for knowledge sharing. - Stay updated on data engineering trends and best practices in GCP technologies. - Contribute to defining and enhancing data governance and management practices within the team. Requirements: - Bachelor's degree in Computer Science, Information Technology, Data Science, or related field. - 3+ years of data engineering experience, with a focus on Google Cloud Platform. - Proficiency in designing and implementing data pipelines using Google Cloud Dataflow, BigQuery, and related tools. - Strong SQL skills, data modeling, and data warehousing experience. - Familiarity with Python or Java for data processing tasks. - Ability to work with structured and unstructured data sources. - Strong analytical and problem-solving skills with attention to detail. - Effective communication of technical concepts to both technical and non-technical stakeholders. Preferred Qualifications: - Google Cloud certifications (e.g., Google Cloud Professional Data Engineer) are highly desirable. - Experience with real-time data processing using Apache Beam and Google Cloud Pub/Sub. - Understanding of CI/CD practices in data engineering workflows. - Knowledge of data visualization tools for effective data insights presentation. (Note: The additional details about benefits like an attractive package, family benefits, visa, and air tickets were not included in the final JD) As a Google Cloud Data Engineer at Mllers Solutions, your primary role will be to enhance data processing capabilities by designing and implementing data pipelines utilizing Google Cloud technologies. You will collaborate with data analysts, business stakeholders, and engineering teams to ensure accurate data processing and availability for analysis and reporting. Key Responsibilities: - Design, develop, and optimize data pipelines using Google Cloud Dataflow, Pub/Sub, and other GCP data services. - Implement data lakes and data warehouses with Google BigQuery for efficient data storage, retrieval, and processing. - Collaborate with data scientists and analysts to understand data requirements and provide business-centric solutions. - Monitor and evaluate data pipeline performance, optimizing and troubleshooting as needed. - Ensure data quality through validation routines and data profiling techniques. - Document data architecture, ETL processes, and operational procedures for knowledge sharing. - Stay updated on data engineering trends and best practices in GCP technologies. - Contribute to defining and enhancing data governance and management practices within the team. Requirements: - Bachelor's degree in Computer Science, Information Technology, Data Science, or related field. - 3+ years of data engineering experience, with a focus on Google Cloud Platform. - Proficiency in designing and implementing data pipelines using Google Cloud Dataflow, BigQuery, and related tools. - Strong SQL skills, data modeling, and data warehousing experience. - Familiarity with Python or Java for data processing tasks. - Ability to work with structured and unstructured data sources. - Strong analytical and problem-solving skills with attention to detail. - Effective communication of technical concepts to both technical and non-technical stakeholders. Preferred Qualifications: - Google Cloud certifications (e.g., Google Cloud Professional Data Engineer) are highly desirable. - Experience with real-time data processing using Apache Beam and Google Cloud Pub/Sub. - Understanding of CI/CD practices in data engineering workflows. - Knowledge of data visualization tools for effective data insights presentation. (Note: The additional details about benefits like an attractive package, family benefits, visa, and air tickets were not included in the final JD)