
Senior Data Engineer
22 hours ago
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.
They will support a wide range of projects while collaborating closely with management teams and business leaders.
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 procedures.
Responsibilities :
- Design, implement, and maintain a scalable Data Lake on GCP to centralize structured and unstructured data from various sources (databases, APIs, cloud storage).- Utilize GCP services including Big Query, Dataform, Cloud Functions, and Cloud Storage to optimize and manage data workflows, ensuring scalability, performance, and security.
- 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).
- Implement best practices for data quality, consistency, and governance across all data pipelines and systems, ensuring compliance with internal and external standards.
- Continuously monitor, test, and optimize data workflows to improve performance, cost efficiency, and reliability.
- Maintain comprehensive technical documentation of data pipelines, systems, and architecture for knowledge sharing and future development.
Requirements :
- Bachelor's degree in Computer Science, Data Engineering, Data Science, or a related quantitative field (e.g Mathematics, Statistics, Engineering).
- 3+ years of experience using GCP Data Lake and Storage Services.
- Certifications in GCP are preferred (e.g Professional Cloud Developer, Professional Cloud Database Engineer).
- Advanced proficiency with SQL, with experience in writing complex queries, optimizing for performance, and using SQL in large-scale data processing workflows.
- Strong programming skills in Python, with additional experience in languages such as Java or Scala encouraged.
- Proven ability to build scalable data pipelines, automate workflows, and integrate APIs for efficient data ingestion.
- Proficient in Git and CI/CD practices, with experience automating testing and deployment of data systems.
- Experience with Looker Enterprise, including developing and maintaining LookML models to enable self-service analytics and data exploration.
- Strong data modeling skills, with experience designing scalable, maintainable models that support analytics, reporting, and business intelligence use cases across diverse teams.
- Expertise in infrastructure automation using Terraform, with experience scripting in Python and Java to provision and deploy cloud resources efficiently.
- 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.
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