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Senior Data Platform Engineer, AWS / Airflow

San Francisco, CA or Seattle, WA - office hybrid

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 approach, and we are looking for a Sr. Data Platform 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 Airflow and related cloud services through AWS. The ideal candidate will have a deep understanding of metadata-driven design approaches, strong software development skills using abstract class methodologies, 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, leveraging services like Airflow, EMR, ECS, S3, Glue, and others.
Implement Data Orchestration: Create and manage data orchestration workflows using Apache Airflow to schedule, monitor, and refine/enhance data processing tasks.
Data Transformation: Enhance the functionality of DBT (data build tool) to integrate into our cloud data platform through custom utility development that integrates with Airflow as well as improvements to our CI/CD processes.
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 pipelines for efficiency, scalability, and cost-effectiveness, additionally leverage abstract class methodology to ensure scalability and performance of our platform.
Security: Ensure data security and compliance with industry standards and company policies, including data encryption, access controls, and auditing.
Collaboration: Collaborate with data engineers, data scientists, analysts, and other partners to understand data requirements and deliver data solutions that meet their needs.
Documentation: Maintain thorough documentation of data engineering processes, pipelines, and architecture.
Problem Solving: Identify and address data engineering challenges, solve issues, and propose innovative solutions.
Stay Ahead Of: 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 engineer, with a focus on AWS cloud platform.

• Strong expertise in Apache Airflow and other related AWS services for data orchestration and transformation.

• Proficiency with programming languages like Python, SQL, and familiarity with relevant SDKs.

• Experience with metadata-driven design approaches, advance software development, and data modeling. Vital to understand sophisticated coding concepts such as abstract classes in Python, and ability to develop custom tooling for data platforms and supporting CI/CD processes.

• Deep knowledge of AWS services such as EC2, S3, Glue, and IAM.

• In depth understanding 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 optimally interact with multi-functional teams.

• AWS certifications (e.g., AWS Certified Data Analytics, AWS Certified DevOps Engineer) are a plus.

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