Data Engineer, PART DataOps

You will lead a team of data engineers to architect, develop, and test large scale and efficient solutions that provide Apple leadership with the accurate data required to rapidly understand and adapt to changing business conditions. We are a growing team with plenty of interesting technical and business challenges to solve. We seek a self-starter who is willing to learn fast, adapt well to changing requirements, develop others, and work with cross functional teams. Lead, mentor, and develop a team of data engineers, setting technical standards and fostering a culture of engineering excellence Design and implement scalable, efficient, and high-quality methods of consuming data from a diverse set of sources with variable quality and predictability Establish and maintain data quality frameworks, including automated validation, monitoring, and alerting Create data products, enabling self-service and predictability by any consumer Build libraries and frameworks that drive leverage and productivity for the entire team Optimize and maintain solutions, driving improvements in efficiency, data quality, and operational excellence Manage team workload and priorities, balancing competing demands while maintaining quality 6+ years software engineering, including strong SQL and data focus BS in Engineering / Computer Science 2+ years leading or mentoring other engineers Expertise in languages like Python and technologies like Airflow, Spark, Trino, Kafka, Docker, Iceberg, Databricks Hands-on experience with database design and architecture in cloud data warehouses and lakehouse environments Ability to analyze complex datasets and design solutions with optimum quality and efficiency Appreciation for data quality and validation in every pipeline Familiarity with SDLC best practices, version control, CI/CD Strong communication skills with the ability to translate between technical and business contexts Experience with cloud services such as AWS, GCP, or Azure for data infrastructure and storage Experience with streaming interfaces and pipelines Finance and accounting process experience

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