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Operations Data Engineer

Apple· Operations
Apply on company site
Austin, TXFull-timePosted 1mo ago

About the role

Apple is seeking an Operations Data Engineer to design and build modern, scalable data infrastructure that powers analytics, machine learning, and AI-driven decision-making across Operations. The role focuses on end-to-end data pipelines, data models, observability, and collaboration with data scientists, ML engineers, software engineers, and analysts to operationalize models and support production AIML workflows in a cloud-based environment.

Responsibilities

  • Engage with business and analytics teams to understand data needs and translate requirements into scalable engineering solutions for Operations decisions
  • Design and implement end-to-end data pipelines and architectures across batch and real-time streaming workloads
  • Build and maintain high-quality data models (dimensional, relational, or knowledge graph-based) using frameworks such as dbt
  • Architect and operate data workflows using orchestration tools (e.g., Apache Airflow) with monitoring, alerts, and SLAs
  • Implement data observability, lineage, validation to uphold data integrity across the platform
  • Collaborate with Data Scientists, ML Engineers, Software Engineers and Analysts to operationalize models and ensure data infrastructure supports production AIML workflows
  • Partner with infrastructure and platform teams to manage cloud-native data environments (Snowflake, Spark, Delta Lake / Apache Iceberg) with emphasis on performance, cost, and scalability
  • Leverage AI-assisted development tools and LLM-powered agents to accelerate pipeline authoring, code review, documentation, and transformation logic generation
  • Apply DataOps principles including CI/CD, version control, automated testing, and containerization (Docker, Kubernetes)
  • Champion a data product mindset enabling self-serve analytics and reducing bottlenecks for downstream consumers
  • Tune query performance, partitioning strategies, and storage optimization for data at scale in cloud warehouses and lakehouses
  • Develop and maintain technical documentation including data dictionaries, lineage diagrams, and architecture decision records
  • Present data infrastructure capabilities, health metrics, and architectural recommendations to senior leadership in clear terms
  • Research and evaluate emerging data engineering technologies including streaming architectures, GenAI-powered tooling, and next-gen warehousing to accelerate innovation

Qualifications

  • MS in Computer Science, Data Engineering, Statistics, Applied Math, Data Science, Operations Research or related field with 8+ years of industry experience OR BS with 10+ years hands-on experience
  • Domain expertise in supply chain, operations management, logistics, planning & forecasting, production integration, channel management
  • Expertise building and operating large-scale ETL/ELT pipelines using Python, SQL, and modern frameworks (dbt, Spark, Kafka/Flink for streaming)
  • Proficiency with cloud data platforms (e.g., Snowflake) and open table formats (Delta Lake, Apache Iceberg)
  • Strong advanced SQL for complex data modeling, query optimization, and analytics engineering
  • Experience with workflow orchestration tools (Airflow or equivalent) and production-grade pipelines
  • Hands-on experience implementing data quality, observability tooling, and data lineage in production
  • Experience with GenAI and Agentic AI tooling including LLM-assisted code generation and AI-powered data pipeline automation
  • Experience with data visualization and self-service analytics platforms (e.g., Tableau, Streamlit, ThoughtSpot) and building light front-end data products
  • Track record of adopting industry best practices and emerging technologies (vector databases, RAG pipelines, AI-native data tools)
  • Ability to work in fast-paced, iterative environments and deliver under timelines
  • Strong communication skills for technical and non-technical audiences
  • Self-sufficient, autonomous, with focus on data integrity and action-oriented delivery

Skills

Required:Data pipeline design and developmentData modelingdbtPythonSQLAirflowSnowflakeDelta Lake / Apache IcebergData observability
Nice to have:Spark/Kafka/Flink
Last updated Sep 4, 2026. Interested? Apply on the company site.

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