Job Description
<p><p>The Senior Data Engineer will help design and implement a Google Cloud Platform (GCP) Data Lake, build scalable data pipelines, and ensure seamless access to data for business intelligence and data science tools.<br/><br/> They will support a wide range of projects while collaborating closely with management teams and business leaders.<br/><br/> The ideal candidate will have a strong understanding of data engineering principles, data warehousing concepts, and the ability to document technical knowledge into clear processes and :</b></p><p><br/></p>- Design, implement, and maintain a scalable Data Lake on GCP to centralize structured and unstructured data from various sources (databases, APIs, cloud storage).<br/><br/></p><p>- Utilize GCP services including Big Query, Dataform, Cloud Functions, and Cloud Storage to optimize and manage data workflows, ensuring scalability, performance, and security.<br/><br/></p><p>- Collaborate closely with data analytics and data science teams to ensure data is properly prepared for consumption by various systems (e.g DOMO, Looker, Databricks).<br/><br/></p><p>- Implement best practices for data quality, consistency, and governance across all data pipelines and systems, ensuring compliance with internal and external standards.<br/><br/></p><p>- Continuously monitor, test, and optimize data workflows to improve performance, cost efficiency, and reliability.<br/><br/></p><p>- Maintain comprehensive technical documentation of data pipelines, systems, and architecture for knowledge sharing and future :</b></p><p><br/></p><p>- Bachelor's degree in Computer Science, Data Engineering, Data Science, or a related quantitative field (e.g Mathematics, Statistics, Engineering).</p><br/></p><p>- 3+ years of experience using GCP Data Lake and Storage Services.<br/><br/></p><p>- Certifications in GCP are preferred (e.g Professional Cloud Developer, Professional Cloud Database Engineer).<br/><br/></p><p>- Advanced proficiency with SQL, with experience in writing complex queries, optimizing for performance, and using SQL in large-scale data processing workflows.<br/><br/></p><p>- Strong programming skills in Python, with additional experience in languages such as Java or Scala encouraged.<br/><br/></p><p>- Proven ability to build scalable data pipelines, automate workflows, and integrate APIs for efficient data ingestion.<br/><br/></p><p>- Proficient in Git and CI/CD practices, with experience automating testing and deployment of data systems.<br/><br/></p><p>- Experience with Looker Enterprise, including developing and maintaining LookML models to enable self-service analytics and data exploration.<br/><br/></p><p>- Strong data modeling skills, with experience designing scalable, maintainable models that support analytics, reporting, and business intelligence use cases across diverse teams.<br/><br/></p><p>- Expertise in infrastructure automation using Terraform, with experience scripting in Python and Java to provision and deploy cloud resources efficiently.<br/><br/></p><p>- Strong communication and collaboration skills, with a proven ability to work cross-functionally with teams such as data science, analytics, product, and business leadership to understand and meet their data needs.</p><br/></p> (ref:hirist.tech)