Data Engineer

The Data Engineer designs, builds, and maintains reliable data pipelines, models, dashboards, and cloud data infrastructure that transform diverse source data into trusted, reusable data products for analytics, research, AI, and business decision-making. This role applies SQL, Python, modern data engineering practices, visualization tools, and AI-assisted development to improve data quality, automate workflows, and deliver scalable data and AI capabilities through internal tools, APIs, and lightweight applications. The position requires strong technical, analytical, communication, and project management skills, with experience in relational databases, cloud platforms, data visualization, and applied AI tools., * Design, build, and maintain scalable, well-tested data pipelines and ELT/ETL workflows using SQL, Python, and cloud data platforms (e.g., BigQuery, Snowflake) to automate data ingestion, cleansing, and transformation

• Model and curate documented, reusable data products (transformations, semantic layers) that analytics, research, and AI systems can depend on
• Create and maintain data visualization dashboards and reports for internal and external use (e.g., Power BI)
• Apply AI tools including large language models (LLMs), AI-assisted coding, and machine learning techniques to solve data problems, accelerate delivery, and improve data reliability, efficiency, and quality
• Partner with research, product, data science, and design teams to incorporate the latest industry and business intelligence and to support their data infrastructure needs
• Document best practices, data models, and current-state data documentation
• Deliver clear, actionable updates and insights to stakeholders, including Executive, Product, Data, and Design teams
• Develop, test, and maintain lightweight applications, internal tools, APIs, and user-facing interfaces on a modern tech stack (e.g., SpringBoot and React.js) to deliver data and AI capabilities to business users
• Develop, construct, test, and maintain cloud data architectures and infrastructure, applying DataOps and DevOps practices such as version control, CI/CD, and infrastructure as code.

• Advanced working SQL knowledge and experience with relational databases, query authoring, and performance tuning, plus working familiarity with cloud data warehouses (e.g., BigQuery, Snowflake)
• Strong programming skills in Python (including Pandas) and demonstrated experience building data pipelines and automation
• Hands-on experience applying AI to real problems prompting and integrating LLMs, using AI-assisted development tools (e.g., GitHub Copilot, Claude, Cursor), and applying ML or statistical methods with sound judgment about where AI does and does not add value
• Familiarity with modern data engineering tooling and practices, such as orchestration (Airflow, Dagster, or similar), transformation frameworks (e.g., dbt), and batch and streaming processing
• Application development capability on a modern stack: building APIs and services (e.g., SpringBoot and React.js) to deliver data and AI features to end users
• Data visualization expertise with proven examples in Power BI or comparable tools
• Experience performing root-cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
• Strong analytical skills working with large, unstructured datasets
• Ability to build processes supporting data transformation, data structures, metadata, dependency, and workload management
• Strong project management, communication, and organizational skills, with the ability to translate business needs into technical solutions, * 2+ years’ experience building data pipelines and working with relational SQL databases
• Proficiency with Python (including Pandas) for data engineering and automation
• Demonstrated experience using AI tools to solve problems e.g., integrating LLMs or LLM APIs, AI-assisted coding, or applying ML in a professional or project setting
• Familiarity with data visualization tools, particularly Power BI or equivalent (Tableau, Sigma, etc.)
• Minimum undergraduate degree in Computer Science, Engineering, or Math (equivalent practical experience considered)
• Preferred graduate degree in Computer Science, Engineering, or Math
• Preferred experience with modern application development on a recent tech stack (e.g., Python/FastAPI or Node.js on the back end; React/TypeScript on the front end); experience with enterprise stacks such as Java/Spring Boot is a plus
• Preferred familiarity with modern data stack tooling (e.g., dbt, Airflow/Dagster) and DataOps practices
• Preferred familiarity with GCP cloud services (BigQuery, Dataform, GCE)
• Preferred familiarity with AWS cloud services (EKS, EC2, RDS, S3, CloudFront, IAM, CloudWatch)
• Preferred familiarity with infrastructure as code (Terraform), GitOps (ArgoCD), container orchestration (Docker/Kubernetes), and CI/CD pipelines (GitLab CI/CD, GitHub Actions)

The people of Aramark proudly serve millions of guests every day through food and facilities in 15 countries around the world. Rooted in service and united by our purpose, we strive to do great things for each other, our partners, our communities, and our planet. We believe a career should develop your talents, fuel your passions, and empower your professional growth. So, no matter what you’re pursuing - a new challenge, a sense of belonging, or just a great place to work - our focus is helping you reach your full potential. Learn more about working here at http://www.aramarkcareers.com or connect with us on Facebook , Instagram and Twitter .