Foodbuy USA is the data and artificial intelligence engine of Compass Group North America, specializing in custom solutions for food service and hospitality. They are seeking a hands-on Master Data Management Data Engineer to design and implement scalable data architectures on AWS, collaborating closely with various teams to manage data pipelines and support analytics.
Responsibilities:
- Design, develop, and deploy scalable and secure data pipelines and cloud-native architectures (data lakes, warehouses, and streaming pipelines) on AWS
- Build and maintain ETL/ELT workflows using AWS Glue, Lambda, and Python to support a variety of data integration needs
- Develop, deploy, and optimize APIs to enable seamless data access for business intelligence, analytics, and operational systems
- Analyze, debug, and resolve data quality issues and pipeline failures to ensure data accuracy and reliability
- Collaborate across teams—including data science, analytics, and software engineering—to design and implement reusable data models
- Ensure efficient, scalable, and secure serverless operations through performance tuning and best practices in AWS environments
- Create and maintain documentation, architecture diagrams, and data flow maps for internal and external use
- Implement and manage data governance, security protocols, compliance standards, and privacy best practices
- Incorporate AI tools, such as ChatGPT, to streamline engineering tasks, documentation, and data exploration
- Lead integration efforts with third-party APIs and data sources to expand the organization’s data capabilities
- Establish and enforce architectural best practices, CI/CD pipelines, and Infrastructure as Code (IaC) in collaboration with DevOps teams
- Mentor team members, stay current with AWS innovations, and champion modern data practices across the organization
Requirements:
- Bachelor's degree in computer science, Information Systems, Analytics, or related field
- 5+ years of experience in data architecture, engineering, or similar roles
- 3+ years of hands-on programming experience with Python
- 3+ years of experience building and managing ETL/ELT data pipelines
- Strong SQL skills and ability to write performant queries across various data stores
- Proficient with AWS services: Lambda, Glue, S3, DynamoDB, Athena, Redshift, and Snowflake
- Solid understanding of OLTP, ODS, and dimensional modeling techniques
- Experience designing APIs and integrating with API-driven data workflows
- Strong knowledge of serverless architecture patterns and best practices
- Excellent problem-solving, analytical, and communication skills
- Experience in agile development environments with CI/CD workflows
- Ability to collaborate across engineering, data, and business teams
- AWS Certifications (e.g., AWS Solutions Architect)
- Experience with modern data stack tools such as dbt, Snowflake, Databricks
- Familiarity with machine learning pipelines and AI-driven analytics
- Experience with Infrastructure as Code (IaC) tools like Terraform or AWS CloudFormation
- Background in DevOps and automated deployment strategies for data workflows
- Experience integrating with ServiceNow application