Data Engineer

Résumé du poste

Design, build, and maintain scalable ETL/ELT data pipelines and APIs within an AWS environment. Collaborate with Data Scientists and Analytic Engineers to ensure data quality and observability using tools like Secoda.

Détails du poste

CDAI is an organization that drives innovation for Compass Group NA, an $18 billion food hospitality organization. Compass Group serves over 3 billion meals per year in award winning restaurants, corporate cafes, hospitals, schools, arenas, museums, and more. As the innovation branch of Compass Group, we’re custom-built for fast-paced transformation at the intersection of hospitality and technology. We’re focused on delivering the best experiences possible for our customers and consumers. WHAT WE DO We are a team of high performing problem solvers with the same vision: to drive the digital future in hospitality. As digital experts we are focused on building a diverse set of products and solutions for our consumers. Our core products include mobile apps, self-serve kiosks, POS and delivery. We also invest in areas like AI, IoT and frictionless retail. Here we work with the “art of the possible” ideas, where we explore and develop the future of hospitality and technology. THE ROLE We are looking for a Data Engineer to join our Data Technology team and help build and maintain scalable data pipelines and APIs. You’ll work with a modern technology stack and collaborate closely with internal and external stakeholders, Data Scientists, and Analytic Engineers to deliver reliable, scalable data solutions. WHAT YOU'LL DO Design, build, and maintain scalable ETL/ELT data pipelines using Python, SQL, Airflow, Spark that hosted in AWS environment. Build and maintain Airflow DAGs, ensuring pipeline reliability and performance. Develop and maintain data APIs and integrations across a variety of data sources. Work with EMR, Iceberg, and Snowflake to support modern data processing and analytics. Ensure data quality, observability, and monitoring across pipelines using tools such as Secoda. Implement data quality checks and monitoring to identify and resolve data issues proactively. Prototype and evaluate new technologies that unlock innovative data-driven consumer experiences. Support stakeholders with data-related technical issues and needs. Experience with Docker, Kubernetes, Spark, Snowflake, CI/CD a bonus WHAT YOU'LL BRING 3–5 years of experience in Data Engineering or a similar role. Strong programming skills in Python and SQL. Hands-on experience with AWS, Lambda, Airflow, and Spark. Experience with Iceberg, EMR, and Snowflake is preferred. Strong understanding of data pipelines, data quality, monitoring, and scalable data architectures. Bachelor's degree or equivalent experience in Computer Science, Computer Engineering, Information Systems, or a related field. Strong communication skills, a collaborative mindset, and a willingness to learn. GOOD TO HAVE Experience with Docker and Kubernetes. Experience with real-time/streaming technologies, such as Kafka, Kinesis Experience with data observability and quality tools, such as Secoda, Data Dog. Experience with CI/CD and modern software development practices.

Ce que vous ferez

Design, build, and maintain scalable ETL/ELT data pipelines and APIs within an AWS environment. Collaborate with Data Scientists and Analytic Engineers to ensure data quality and observability using tools like Secoda.

Exigences

Requires 3-5 years of experience in Data Engineering with strong proficiency in Python, SQL, and AWS services. A Bachelor's degree in Computer Science or a related field is required.

Compétences indiquées

• Kubernetes · Souhaitée
• SQL · Souhaitée
• CI/CD · Souhaitée
• Docker · Souhaitée
• Amazon Web Services · Souhaitée
• Python · Souhaitée

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Python
• SQL
• AWS
• Airflow
• Spark
• Snowflake
• ETL/ELT
• Iceberg
• EMR
• Docker
• Kubernetes
• CI/CD
• Data APIs
• Data Quality
• Data Observability
• Kafka

Domaines d’emploi

• Data & Analytics
• Technology
• Engineering
• Software
• Hospitality