Data Engineer
Summary
Architect, develop, and optimize large-scale data solutions and self-service data products, working with SQL, Python/Java/Scala, and big data tools like Spark, Kafka, and Airflow on cloud infrastructure.
Description
You will architect, develop, and test large scale and efficient solutions that provide senior management with the accurate data to make business decisions
Design and implement scalable and high-quality methods of consuming data from a diverse set of sources with variable quality and predictability Create data products, enabling self-service and predictability by consumer Build libraries and frameworks that drive leverage and productivity for the team Optimize and maintain solutions, driving improvements in efficiency, data quality, and operational excellence
Requirements
BS or MS in Engineering/Computer Science 6+ years software engineering, including strong SQL and data focus Expertise in languages like Python, Java, or Scala and technologies like Airflow, Spark, Trino, Kafka, Docker, Iceberg Ability to analyze complex datasets and design solutions with quality and efficiency Familiarity with SDLC best practices, version control, CI/CD Experience with cloud services such as AWS, GCP, or Azure for data infrastructure and storage Knowledge of infrastructure as code (e.g., Terraform) and container orchestration tools (e.g., Kubernetes)
You will architect, develop, and test large scale and efficient solutions that provide senior management with the accurate data to make business decisions
Design and implement scalable and high-quality methods of consuming data from a diverse set of sources with variable quality and predictability Create data products, enabling self-service and predictability by consumer Build libraries and frameworks that drive leverage and productivity for the team Optimize and maintain solutions, driving improvements in efficiency, data quality, and operational excellence
Requirements
BS or MS in Engineering/Computer Science 6+ years software engineering, including strong SQL and data focus Expertise in languages like Python, Java, or Scala and technologies like Airflow, Spark, Trino, Kafka, Docker, Iceberg Ability to analyze complex datasets and design solutions with quality and efficiency Familiarity with SDLC best practices, version control, CI/CD Experience with cloud services such as AWS, GCP, or Azure for data infrastructure and storage Knowledge of infrastructure as code (e.g., Terraform) and container orchestration tools (e.g., Kubernetes)