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.