["DE Senior Architect","DE Senior Architect"]

Role: DE Senior Architect

Location: Seattle, WA USA

Type: Full time

Job description

Job Overview:

As a DE Senior Architect specializing in GCP Composer within our Retail vertical, you will lead the design and implementation of scalable, robustdata engineering solutions.

Success in this role means driving high-impact cloud data pipelines that optimize data workflows and empower actionable business insights.

You will collaborate closely with data scientists, analysts, and software engineers to embed AI capabilities into retail operations.

This role plays a critical part in advancing Tredence's mission of delivering practical AI solutions that transform client businesses.

What will your role look like? - Design and architect end-to-end data pipelines and workflows leveraging Google Cloud Platform technologies, including Composer, BigQuery, BigTable, DataFlow, DataProc, and DataStore.

Lead data engineering initiatives by building scalable, optimized ETL/ELT solutions using Python and SQL to enable efficient data processing and analytics.

Collaborate with cross-functional teams to ensure seamless integration of data solutions with AI and business analytics applications.

Implement DevOps practices to automate deployment, monitoring, and management of data workflows on GCP.

Troubleshoot and optimize existing data pipelines for performance, reliability, and cost-efficiency.

Mentor junior engineers and promote best practices in cloud-native data engineering within the team.

You will need: -

Demonstrate 10-15 years of experience in designing and implementing complex data engineering architectures, preferably within the retail industry.

Possess in-depth expertise in Google Cloud Platform services, particularly Composer, BigQuery, BigTable, DataFlow, DataProc, and DataStore.

Apply strong programming skills in Python and advanced proficiency in SQL for data manipulation and pipeline orchestration.

Utilize DevOps methodologies and tools to streamline CI/CD pipelines and infrastructure automation on Google Cloud.

Hold a Bachelor's degree in Computer Science, Engineering, or a related technical field.

Exhibit excellent problem-solving abilities and effective communication skills to engage with both technical and non-technical stakeholders.

Good to Have Skills:

Gain additional value from certifications such as Google Cloud Professional Data Engineer or Google Cloud Professional Cloud Architect.

Demonstrate familiarity with containerization technologies (e.g., Docker, Kubernetes) to enhance deployment flexibility.

Leverage knowledge of other cloud platforms or hybrid cloud environments to support multi-cloud strategies.

Possess experience with machine learning pipelines or MLOps frameworks to bridge data engineering with AI/ML workflows.

Contribute to open-source projects or publish technical content related to cloud data engineering best practices.