Data Engineer – Cloud & Real‑Time Pipelines

About the role

The Data Engineer will design, build and maintain scalable batch and real‑time data pipelines on Amazon Web Services. Working in a hybrid setting, you will enable data‑driven decisions across the business, especially for customer acquisition, operational performance and sports‑betting analytics.

Key responsibilities

• Design, develop and maintain scalable batch and real‑time pipelines using ELT processes.
• Build and operate cloud data infrastructure with Amazon S3, AWS Glue, AWS Lambda and Amazon Redshift.
• Implement orchestration and scheduling with Apache Airflow or Amazon MWAA.
• Develop data transformations and models using SQL and dbt.
• Integrate streaming solutions with Apache Kafka and Apache Spark.
• Ensure reliability, performance and scalability of production pipelines.
• Participate in an on‑call rotation to monitor and resolve high‑priority issues.
• Apply secure data handling practices and manage access controls.
• Support data governance, quality and compliance with internal policies.
• Collaborate with data architects, product teams, analysts and IT in agile sprints.

Required profile

• Proven experience designing and maintaining batch and real‑time data pipelines.
• Hands‑on experience with AWS services such as S3, Glue, Lambda and Redshift.
• Strong SQL skills and familiarity with data modelling tools like dbt.
• Experience with orchestration tools (Apache Airflow or Amazon MWAA).
• Knowledge of streaming technologies such as Kafka and Spark.
• Ability to work in an agile environment and collaborate with cross‑functional teams.
• Willingness to participate in on‑call rotation for production support.

Required skills

• Amazon S3
• AWS Glue
• AWS Lambda
• Amazon Redshift
• Apache Airflow / Amazon MWAA
• SQL
• dbt
• Apache Kafka
• Apache Spark
• Snowflake (integration)