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Apple Senior Data Engineer WW Channel Strategy & Operations United States, Texas, Austin 785783476
31.03.2025
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In this role, you will:- Develop and drive customer-focused solutions based on developing a deep understanding of user requirements- Translate user needs into actionable solutions and act as a subject matter expert in customer discussions- Scope and prioritize system development with a focus on incremental delivery and an iterative approach, ensuring adaptability to evolving project requirements- Design and implement modern, distributed data architectures aligned with data mesh principles (domain ownership, product thinking, self-serve platforms, and federated governance)- Lead the development and deployment of data products across business domains, ensuring scalability, interoperability, and reliability- Collaborate with domain teams to define and build domain-aligned data models, pipelines, and APIs- Architect cloud-native data platforms using tools and services such as Databricks, Snowflake, AWS/GCP/Azure, Kafka, Delta Lake, etc.- Define and enforce data governance, metadata management, quality, lineage, and observability standards- Partner with cross-functional teams (Data Scientists, Product Managers, Business Units) to translate business needs into technical solutions- Evaluate, recommend, and integrate new tools, frameworks, and practices to improve the data architecture and engineering ecosystem- Drive automation, CI/CD practices, and Infrastructure-as-Code (IaC) for data solutions
- Bachelor’s or Master’s degree in Computer Science, Information Systems, Software Engineering, Data Science, or a related field
- 12+ years industry experience in data engineering or related technical field
- 5+ years experience in building and maintaining large-scale ETL/ELT pipelines (batching and/or streaming) that are optimized for performance and can handle data from various sources, structured or unstructured
- Experience developing automation to write and read data from relational, no-SQL databases, from cloud storage and external data sources
- Hands-on experience in the realm of large-scale data processing infrastructure, including building and maintaining API-driven services
- Strong hands-on programming skills with a track record of developing robust, scalable, and maintainable codebases for intricate data infrastructure
- Ability to lead technical discussions about data architecture and data integration
- Familiarity with other related fields, such as data science, machine learning, and artificial intelligence, to design solutions that can accommodate advanced analytics
- Familiarity with a diverse set of technologies, including but not limited to Spark, Flink, Trino, Kafka, Iceberg, in the big-data ecosystem
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