Senior / Lead Data Platform Engineer

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About Salesforce

We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place.

Salesforce is on a transformative journey, one that focuses on delivering unparalleled customer success and propelling our growth. Central to this journey is the establishment of a robust data foundation, essential for all our core marketing functions, powered by intelligent data products. The Salesforce Marketing Analytics Platforms team is spearheading this initiative, using data to inform and influence our decision-making processes.

The Marketing Decisions Science team is working to rebuild and modernize our data architecture with a cloud first approach and leveraging code reusability through a standardized metadata driven approach and we are looking for an experienced 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 Apache Airflow and related cloud services through AWS. The ideal candidate will have a deep understanding of metadata-driven design approaches, strong software development skills leveraging abstract class methodologies, and a passion for creating 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, SQS, SNS, S3, Glue, and others.

• Implement Data Orchestration: Create and manage data orchestration workflows using Apache Airflow to schedule, monitor, and optimize data processing tasks.

• Software Engineering: Python, Java, with strong software engineering skills, specifically in abstract class driven design, infrastructure as code (Iac), and object oriented programming (OOO). 

• 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 monitor and optimize data pipelines for efficiency, scalability, and cost-effectiveness, additionally leverage abstract class methodology to ensure scalability and performance of our platform.

• 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 engineers, data scientists, analysts, and other stakeholders 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, troubleshoot issues, and propose innovative solutions.

• Stay Current: Stay up-to-date with industry trends, best practices, and emerging technologies in data engineering and cloud computing.

Qualifications:

• Bachelor's degree in Computer Science, Information Technology, or a related field along with 6+ years of relevant experience in the field.

• Proven experience as a data platform engineer, with a focus on AWS cloud platform.

• Strong expertise in Apache Airflow and 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. Necessary to understand advanced 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.

• 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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