Cloud Data Engineer ROCGJP00027944 A leading biotechnology company is seeking a highly skilled and motivated Cloud Data Engineer to join our growing data team. The ideal candidate will have a strong background in developing data pipelines, implementing data models, and executing best practices for developing data products. This role requires expertise in AWS, GitLab CI/CD, dbt, Snowflake, SQL, Python, Git, and DevOps, as well as hands-on experience with orchestrators such as Airflow and AutoMateNow, and data governance technologies like Monte Carlo and Collibra. Cloud Data Engineer Pay and Benefits: • Hourly pay: $70-$80/hr (pay varies based on candidate's experience) • Worksite: Leading biotechnology company (South San Francisco, CA 94080) • W2 Employment, Group Medical, Dental, Vision, Life, Retirement Savings Program, PSL • 40 hours/week, 7 Month Assignment Cloud Data Engineer Responsibilities: • Develop Data Pipelines: Design, develop, and maintain robust, scalable, and efficient ETL/ELT pipelines to support diverse data sources and large-scale data processing. • Data Modeling: Create and maintain data models and data architecture to ensure data integrity and optimum performance. • Best Practices Implementation: Apply industry best practices in data warehousing, data governance, and data lifecycle management. • Collaboration: Work closely with data scientists, analysts, and other stakeholders to gather requirements and deliver high-quality data products. • Automation and CI/CD: Implement CI/CD pipelines using GitLab for automated testing, deployment, and integration of data workflows. • Database Management: Manage and optimize Snowflake databases for performance, scalability, and cost-effectiveness. • Coding and Scripting: Write efficient SQL queries and Python scripts to extract, load, and transform data. • Version Control: Utilize Git for version control, ensuring traceable and manageable code changes. • Orchestration: Utilize orchestration tools like Airflow and AutoMateNow to manage and automate data workflows. • Data Governance: Implement and manage data governance and data observability solutions using technologies like Monte Carlo and Collibra. • Monitoring and Optimization: Monitor data pipeline performance and troubleshoot issues to ensure reliability and efficiency. • Documentation: Maintain comprehensive documentation for data pipelines, models, and processes. Cloud Data Engineer Qualifications: • 5+ years of experience in data engineering or a similar role. • Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field. • AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect. • Proven experience with AWS cloud services related to data processing, such as S3, Redshift, Lambda, Glue, and Data Pipeline. • Proficiency in designing and implementing CI/CD pipelines with GitLab. • Experience with dbt (data build tool) for transforming data within the warehouse. • Experience with orchestrators like Airflow and AutoMateNow. • Experience with real-time data processing and streaming technologies (e.g., Kafka, Kinesis). • Experience in a regulated industry • Experience in a manufacturing environment • Strong knowledge of Snowflake with hands-on experience in data warehousing solutions. • Expertise in SQL for data querying, manipulation, and optimization. • Proficiency in Python for scripting and automation tasks. • Familiarity with DevOps practices and tools. • Knowledge of data governance and observability tools such as Monte Carlo and Collibra. • Strong working knowledge of Git for version control. • Strong problem-solving and analytical skills. • Excellent communication skills, both written and verbal. • Ability to work collaboratively in a fast-paced, dynamic environment. • High attention to detail and commitment to producing high-quality work.