Full stack Application Developer

Additional Skills

Architecture and Design Skills Modular, service-oriented architecture separating web UI, APIs, background workers, and ETL components API-first design to support future expansion beyond Dash-based frontends Performance-aware architecture including server-side aggregation, streaming, backpressure handling, and cost-efficient scaling Reliable job orchestration with retry mechanisms, dead-letter queues, and idempotency for long-running analytics tasks Strong documentation practices using MkDocs or Sphinx, and collaborative development through code reviews and design documentation Technical Skills Required

Core Technical Skills Backend and APIs Expert-level Python with strong skills in performance optimization and profiling tools like cProfile and py-spy Production-grade API development using FastAPI or Flask, with REST/JSON and OpenAPI design principles Asynchronous and background job handling using Celery, RQ, Dramatiq with Redis/RabbitMQ, Azure Durable Functions, or Azure Service Bus Concurrency and parallelism using asyncio, multiprocessing, and distributed computing frameworks like Dask or Ray Caching and session management using Redis, with a focus on idempotent job design Frontend/UI for Analytics Strong experience with Angular 2+ and Dash/Plotly, including state management, callback optimization, memoization, and pattern-matching callbacks High-performance data visualization using Plotly WebGL, plotly-resampler, Datashader, or HoloViews, with server-side downsampling and aggregation Data Engineering and Pipelines Secure ingestion of encrypted files using PGP/AES, with signature verification and integrity checks Key and secret management using HashiCorp Vault or cloud KMS, including RBAC, auditing, and rotation ETL orchestration and scheduling using Airflow or Prefect, with SLA enforcement and retry logic Database design and optimization using Postgres, TimescaleDB, or ClickHouse, with strong SQL skills, indexing, partitioning, and familiarity with Microsoft Fabric

Experience Guidelines

Extensive experience (6+ years) building production-grade Python data applications At least 2 years of hands-on experience with Angular/Dash/Plotly in production environments Proven delivery of horizontally scalable systems with background job processing Demonstrated implementation of performance-critical analytics using tools like Numba, Cython, Rust, Polars, or distributed compute frameworks Preferred qualifications

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field, or equivalent practical experience Our commitment

We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results. Lam Research ("Lam" or the "Company") is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees. Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories – On-site Flex and Virtual Flex. ‘On-site Flex’ you’ll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. ‘Virtual Flex’ you’ll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.