at Apple
Location
Cupertino, United States of America
Compensation
$119k–$198k USD
Type
full time
Posted
1 weeks ago
Market range · company + function + seniority
p25 · target · p75 · n=138
Posted $198k · well below market
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We are looking for a senior, business- and data-minded engineer with a passion for building intuitive applications that solve real-world business problems. This role sits at the intersection of data engineering, software development, applied AI, and business analysis.
You will design, build, and deploy lightweight web interfaces and data tools — primarily using Python frameworks like Streamlit — to streamline financial analysis, reporting, and decision-making. You’ll also help lead our team’s adoption of AI: both inside our own engineering practice and in the products we ship to analysts, helping them think through where AI can have the biggest impact in their own workflows.
Success in this role requires someone who can quickly absorb complex financial processes, translate ambiguity into a technical roadmap, and deliver high-quality, user-friendly applications with minimal oversight — while raising the bar for the engineers and analysts around them.
Own complex projects end-to-end with minimal direction — from discovery and scoping through design, development, deployment, and long-term maintenance
Partner with financial analysts and Finance leadership to deeply understand workflows and pain points, and proactively identify high-leverage opportunities for automation and AI
Design, develop, and deploy data applications (primarily Streamlit) that automate tasks, visualize data, and improve the efficiency of financial processes
Lead the team’s adoption of AI — both in our own engineering practice (AI-assisted development, agentic tooling) and in the products we ship (LLM-powered features, RAG, agents, intelligent automation)
Coach financial analysts on where and how to apply AI in their own workflows, helping them separate hype from real opportunity and prototype solutions together
Write clean, well-documented, maintainable Python — and establish patterns and reusable components others on the team can build on
Connect applications to a variety of data sources (databases, APIs, data lakes) across Apple’s data ecosystem
Architect for reliability: robust error handling, logging, monitoring, CI/CD, and security-by-default
Gather user feedback and iterate to continuously improve usability and impact
Partner with data scientists to integrate analytical and ML models into applications
Set technical standards and mentor other engineers on the team
Document applications, data flows, architecture decisions, and technical specifications
6+ years in data engineering or software development, with a strong track record of shipping production data applications end-to-end
Expert proficiency in Python and hands-on experience building and deploying web applications with Streamlit
Strong experience with relational databases (e.g., SQL Server, PostgreSQL) and modern data lake / lakehouse environments
Strong software engineering fundamentals: Git, code review, testing, CI/CD, observability
BS in Computer Science, Data Science, Engineering, or a related field
Hands-on experience building with modern AI/LLM tooling — e.g., OpenAI / Anthropic APIs, RAG pipelines, agent frameworks, MCP, prompt engineering — and a clear point of view on where AI does and doesn’t belong in business workflows
Demonstrated use of AI-assisted development tools (e.g., Claude Code, Cursor, Copilot) to ship higher-quality software faster
Experience with FastAPI (or Flask/Django) for building Python web services and APIs
Experience with React or another modern front-end framework for building richer UIs beyond Streamlit
Proficiency with data visualization libraries (Plotly, Matplotlib, Seaborn) and an eye for usable, well-designed UIs
Solid grasp of data warehousing concepts and ETL/ELT design
Experience leading projects or mentoring engineers in a senior IC capacity
Experience shipping LLM-powered features to production (not just prototypes)
Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes)
Background working with Finance, FP&A, or Sales Finance teams
Strong communication skills with the ability to translate between technical and business contexts
The people here at Apple don’t just create products — they create the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts.
Apple is seeking a senior, hands-on Data Engineer to join the Next-Gen Workflow team within our Finance Process, Analytics, Reporting & Technology (PART) Data Operations group. You’ll design and build the data applications — and increasingly, the AI-powered experiences — that change how Apple’s Finance analysts work every day. This is a role for an engineer who wants to operate independently end-to-end, help define what AI-native finance tooling looks like at Apple, and see their work used by key stakeholders across the organization.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant
At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
Learn about accessibility in Apple’s workplace
Learn about reasonable accommodations for job applicants
Apple accepts applications to this posting on an ongoing basis.
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