Senior Data Engineer
Apple
Data Science
Jersey City, NJ, USA
USD 181,100-272,100 / year + Equity
Posted on May 22, 2026
At Apple, we believe in creating products that enrich people’s lives in extraordinary ways. Our teams are at the cutting edge of technology, designing and building the software that powers our global ecosystem of devices and services. If you’re a passionate engineer who thrives in a fast-paced, collaborative environment and wants to contribute to world-class tools used by hundreds of millions of people, we’d love to hear from you.
We are seeking a talented Senior Data Engineer to join our dynamic team. In this hybrid data engineering and backend development role, you will collaborate across functions to design, build, and deploy end-to-end solutions for data acquisition, processing, analytics, and visualization. You’ll continuously identify opportunities to extract deeper insights from existing data, source new data streams, and rigorously validate data quality and processing pipelines. You’ll also build custom, interactive visualizations and partner with product teams to integrate analytics and reporting directly into web applications. If you bring deep expertise in Python, SQL, and event-driven messaging, strong backend skills in Go, and hands-on experience with D3.js visualization, this is a unique opportunity to drive meaningful impact atone of the most innovative companies in the world.
- Design, develop, and maintain scalable data pipelines and backend micro services using Python and Go.
- Manage structured and unstructured data flowing through PostgreSQL, Snowflake, S3, and NATS messaging infrastructure.
- Build custom, interactive data visualizations using D3.js to power internal dashboards and user-facing analytics features.
- Write highly optimized SQL queries and administer PostgreSQL databases, including schema design, advanced data modeling, and query performance tuning.
- Architect and integrate event-driven systems using NATS for real-time streaming, batch processing, and reliable inter-service communication.
- Refactor and modernize legacy backend codebases to improve performance, security, and long-term maintainability.
- Own features end-to-end: from technical design and development to testing, deployment, and monitoring.
- Collaborate with cross-functional teams on REST/async API design, debugging, and system performance optimization.
- Actively participate in code reviews, technical architecture discussions, and engineering best practices.
- Stay current with emerging data engineering and backend technologies, proposing and implementing improvements to our development workflows.
- Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or equivalent practical experience.
- 5+ years of professional software engineering experience with a strong focus on data infrastructure and backend development.
- Advanced proficiency in Python for data engineering, including experience with Pandas/Polars, orchestration tools (Airflow, Dagster, or Luigi), and Pydantic for data validation.
- Strong proficiency in Go for backend service development, with a preference for idiomatic, standard-library-driven architecture.
- Expert-level SQL skills, particularly in PostgreSQL, including complex query optimization, indexing strategies, and database administration.
- Proven experience developing and deploying D3.js visualizations in production web applications.
- Demonstrated track record of building, testing, and deploying backend CRUD services in high-availability production environments.
- Ability to work independently, troubleshoot complex data or backend issues, and deliver complete features from conception to production.
- Hands-on experience refactoring legacy systems to improve code quality, performance, and observability.
- Experience translating ambiguous business requirements into clear, scalable technical solutions.
- Familiarity with OpenAPI/Swagger for REST APIs and AsyncAPI for event-driven services.
- Experience implementing observability stacks using Prometheus metrics and OpenTelemetry/Jaeger distributed tracing.
- Deep understanding of message brokers (NATS, Kafka, Redis Streams) and stream processing patterns.
- Experience with cloud object storage (S3-compatible) and caching layers (Redis-compatible).
- Proficiency with CI/CD pipelines, containerization (Docker), and infrastructure-as-code concepts.
- Strong grasp of Agile development practices and Git-based version control workflows.
- Genuine passion for Apple’s ecosystem and a user-first mindset in engineering decisions.