Senior Software Engineer, SDLC Analytics

Do you love building elegant systems that make engineering teams measurably better Do you like transforming complex data into actionable insights Are you passionate about applying software engineering rigor to the measurement and optimization of the development lifecycle itself As part of our Software Development Life Cycle (SDLC) team youll architect and engineer a comprehensive telemetry and analytics platform that provides deep telemetry across the entire software development lifecycle. Your work will empower engineering teams across Apple to quantify their performance identify bottlenecks through engineered observability and continuously improve their development workflows.

We are seeking an experienced Software Architect or Senior Software Engineer with a strong data analytics background in building data-intensive systems to join our team. The ideal candidate brings production-grade software engineering discipline to data systems Architecting data models for our scalable SDLC event platform that serves as the backbone for data pipelines and engineering scalable data infrastructure and analytics capabilities across one of the worlds largest software software development at Apple spans multiple specialized platforms source control build system deployment orchestration artifact management and observability tooling. Each generates rich telemetry but analyzing these signals in isolation yields limited insight. Youll solve this by engineering a unified analytics platform that correlates events across the entire development pipeline turning fragmented data into a coherent picture of engineering effectiveness.n

Data Model u0026 Schema Engineering: Engineer unified schemas representing SDLC entities and events across all platforms. Define and standardize event contracts using Apples CDEvents specification model relationships between applications services deployments and incidents and architect a data model that cleanly supports both real-time streaming and batch analytics Platform Integrations: Design for fault tolerance and schema evolution. Design build and own data pipelines that reliably ingest events from source control build systems deployment services test platforms artifact registries and monitoring systems. Leverage the CDEvents Platform architecture for event ingestion implement robust validation and enrichment pipelines and handle both real-time streaming (Kafka) and API-based data access patterns with production-quality reliability and Infrastructure u0026 Database Architecture: Architect and implement scalable database solutions optimized for SDLC analytics including time-series storage for deployment events and metrics dimensional modeling for applications and teams event streaming for real-time dashboards and a data warehouse layer for historical analysis and trend identification. Apply software engineering best practices: versioning testing CI/CD and operational Tooling u0026 Reporting: Build first-class analytics capabilities to measure engineering effectiveness through DORA metrics (Deployment Frequency Lead Time to Change Change Failure Rate Mean Time to Recover). Partner with stakeholders to deliver intuitive visualizations implement anomaly detection and ship custom analytics tooling that drives continuous improvement across engineering organizations.

Minimum 4 years of relevant industry experiencenStrong software engineering foundation with significant experience building and operating production data systemsnProven track record of designing shipping and maintaining internal or external data-intensive products end-to-endnDeep expertise in data modeling including time-series and dimensional modeling approachesnHands-on experience with event streaming platforms (e.g. Kafka) and pipeline orchestration frameworks (e.g. Airflow Spark)nProficiency in Java; strong SQL skills for data modeling and pipeline development; comfort working across the full data stack from ingestion to servingnSolid understanding of database technologies for both operational and analytical workloadsnBS in Computer Science Computer Science or a related technical field

Experience building analytics or telemetry platforms for software development workflowsnHands-on familiarity with SDLC tooling Git build systems CI/CD pipelines deployment orchestrationnStrong software design skills: ability to write clean testable maintainable code in a collaborative engineering environmentnSome experience using AI-powered solution on analyzing CI/CD datanStrong problem-solving and analytical skillsnAbility to work well in a team and communicate effectively with both technical and non-technical stakeholdersnSelf-motivated and well-organized with a demonstrated ability to take ownership and drive ambiguous projects to completion