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Senior Data Engineer

Apple
Posted 2 days ago, valid for 8 days
Location

Jersey City, NJ 07302, US

Salary

Competitive

Contract type

Full Time

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Sonic Summary

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  • Apple is seeking a talented Senior Data Engineer with 5+ years of professional software engineering experience.
  • The role involves designing, building, and deploying end-to-end solutions for data acquisition, processing, analytics, and visualization.
  • Candidates should have advanced proficiency in Python and SQL, strong backend skills in Go, and hands-on experience with D3.js visualizations.
  • A Bachelor's degree in Computer Science, Software Engineering, or Data Engineering is required, along with a passion for Apple's ecosystem.
  • The position offers a competitive salary, reflecting the candidate's experience and expertise in the field.
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.

Description


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.

Minimum Qualifications


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.

Preferred Qualifications


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/Jaegerdistributed 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.



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