Senior Data Platform Architect

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Job Category

Software Engineering

Job Details

About Salesforce

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Position Overview:

The Marketing Decisions Science team is working to rebuild and modernize our data architecture with a cloud first approach and using code reusability through a standardized metadata driven methodology, and we are looking for an expert Data Platform Architect/Engineer to join our team. This role is responsible for designing, building, and maintaining data engineering architecture on the AWS cloud platform, with a strong focus on tools like Apache Airflow, ECS, Lambas, and dbt. A strong skillet and experience with OOP in Python and class abstraction is a must. The ideal candidate will have a deep understanding of metadata-driven design approaches and a passion for crafting scalable and efficient data pipelines.

Key Responsibilities:
Architect and Build Data Engineering Infrastructure: Design, develop, and maintain data engineering infrastructure on AWS, using services like ECS, S3, Glue, and others.
Implement Data Orchestration: Create and manage data orchestration workflows using Apache Airflow to schedule, monitor, and optimize data processing tasks and additional tooling.
CI/CD: Develop and maintain proper CI/CD processes for the data platform and supported engineering services (dbt, Sagemaker Pipelines, etc.)
Data Observability: Through tools like dbt, and others, build out observability of the data platform and its components.
Metadata-Driven Design: Implement and advocate for metadata-driven design principles to enhance data lineage, documentation, and data governance.
Optimize Performance: Continuously supervise and optimize data platform for efficiency, scalability, and cost-effectiveness.
Security and Compliance: Ensure data security and compliance with industry standards and company policies, including data encryption, access controls, and auditing.
Collaboration: Collaborate with data scientists, engineers, security, analysts, and other partners to understand data requirements and deliver data platform solutions that meet their needs.
Documentation: Maintain thorough documentation of data engineering processes, pipelines, and architecture.
Problem Solving: Identify and address data engineering challenges, tackle issues, and propose innovative solutions.
Stay Current: Stay up-to-date with industry trends, standard processes, and emerging technologies in data engineering and cloud computing.
Qualifications:

• A related technical degree.
• Proven experience as a data platform architect and engineer, with a focus on AWS, IaC, OOP in Python
• Strong expertise in Apache Airflow and dbt for data orchestration and transformation.
• Proficiency with programming languages like Python, SQL, Terraform, and familiarity with relevant SDKs.
• Experience with metadata-driven design approaches and data modeling.
• Deep knowledge of AWS services such as EC2, S3, Glue, and IAM.
• Deep knowledge of Infrastructure as Code (IaC), Terraform preferred.
• Understanding of data governance, security, and compliance principles.
• Excellent problem-solving skills and the ability to work collaboratively in a team.
• Strong communication skills to effectively interact with cross-functional teams.
• AWS certifications (e.g., AWS Certified Data Analytics, AWS Certified DevOps Engineer) are a plus.

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