Lead Data Engineer

asco; Alexandria (VA); Hybrid; USD 150,000 - 210,000; Full time

Job summary

ASCO in Alexandria, VA, seeks a Lead Data Engineer to shape data-driven solutions. You will architect and deploy scalable batch and streaming pipelines across multi-cloud environments (GCP, AWS, Azure) to unify enterprise data.

This hands-on role requires writing production-grade Python code, building AI/ML pipelines, and establishing MLOps, CI/CD, and observability to support AI agents and analytics. You will mentor teammates, define engineering standards, review code, and partner with product

Qualifications

• Bachelor's degree or equivalent in a technical field.
• 9+ years building enterprise-grade data pipelines (batch/streaming).
• 2+ years deploying AI/ML solutions including RAG architectures.
• Strong Python and modern data/software practices.

Responsibilities

• Architect and deploy scalable data pipelines in multi-cloud environments.
• Develop production-grade code and APIs for data products and AI agents.
• Lead engineering standards, code reviews, and mentorship for junior engineers.
• Ensure security, reliability, and data integrity across platforms.
• Optimize platform cost and performance while accelerating the digital roadmap.

Skills

Python

Cloud architecture

Data pipelines

LLM integration

MLOps

Team leadership

Education

Bachelor's degree in CS or related field

Tools

BigQuery

Vector databases

CI/CD tooling

Job description

Are you interested in making a world of difference in cancer care? Cancer strikes more than 10 million people worldwide each year. As the leading medical society representing doctors who care for people with cancer, the American Society of Clinical Oncology (ASCO) is committed to conquering cancer through research, education, and promotion of the highest quality care.

Who we are:

ASCO is a flexible, high-performance membership organization where employees collaborate to support our mission through evidence, care, and impact. Together with Conquer Cancer, the ASCO Foundation, we foster a culture that prioritizes customer‑centricity, emphasizes teamwork, and commits to quality. Our culture, ASCO Works - Our Way of Working, has long enabled workplace flexibility and embraced technology to help us achieve balance. To learn what it's like to work at ASCO, click here .

Total Rewards:

At ASCO, we offer a competitive and comprehensive total rewards package. Our compensation philosophy and structure ensure that pay remains market-based, tied to performance, and aligned with our core values. The hiring salary range displayed accounts for a broad spectrum of factors, and the final offer will depend on an evaluation of the selected candidate's experience, training, and specialized skill sets.

In addition to base pay, this position is eligible for our robust total rewards package, which includes health, vision, and dental insurance, a 401(k) with generous contribution, health and wellness benefits, family forming benefits, education support program, generous leave, and much more!

Who we are looking for:

ASCO is in search of a high-performing Lead Data Engineer to play a vital role as a hands‑on architect and engineer turning complex data into strategic business value. This role is responsible for actively writing code, building scalable data pipelines, pioneering responsible AI practices, and deploying production‑grade solutions for AI/ML, BI, and operations. The position will solve data engineering challenges, elevate technical standards, and lead through code.

This position is hybrid with a primary location at our headquarters in Alexandria, VA. The hire must reside within 75 miles of our headquarters. We anticipate the hire to be onsite approximately 1-2 days per week.

Responsibilities

• Architect & Deploy Scalable Data Pipelines/Products : Design, build, and optimize production‑grade batch and streaming data pipelines in a multi‑cloud (GCP, AWS, Azure) ecosystem to unify enterprise data assets into a high-performance AI, analytics, and operational foundation.
• Simple to Complex Data Pipelines : Design, build, and optimize scalable batch and streaming data ingestion pipelines for both structured and unstructured data.
• Trusted Context Foundation : Ensure all developed solutions meet high standards for security, quality, reliability, explainability, and maintainability.
• Engineer Agentic AI & RAG Workflows : Build and operationalize modern AI capabilities-including RAG, semantic search, vector databases, autonomous multi‑agent workflows, grounded in clean enterprise context.
• Establish MLOps & LLMOps Rigor: Build CI/CD, containerization, and observability frameworks to streamline LLM service integrations for fast, reliable, and cost‑effective application delivery.
• Write Production‑Grade Code & APIs: Deliver clean, maintainable Python code and microservices that integrate data products directly into AI agents, business applications, and operational workflows.
• Optimize Platform Cost & Performance: Continually refine database designs, storage tiers, and compute workloads to maximize query speed while actively optimizing cloud operating costs (OpEx).
• Translate Strategy into Execution: Partner with product leads and business stakeholders to translate mission goals into scalable technical solutions that accelerate the digital roadmap.
• Lead Through Code & Technical Mentorship: Set engineering standards, drive rigorous code reviews, and elevate team capability by actively building alongside junior and mid‑level data engineers.
• Ensure Operational Reliability & Incident Health: Perform root‑cause analysis and rapid remediation for complex data platform incidents to maintain continuous system availability and data integrity.

Required Education and Experience

• Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Applied Mathematics, or a related technical field (or equivalent practical experience).
• 9+ years of hands‑on experience architecting, building, and maintaining enterprise‑grade batch and streaming data pipelines in modern cloud environments.
• 2+ years of hands‑on experience building and deploying production‑grade AI/ML solutions, including RAG architectures, vector databases, LLM integrations, and agentic workflows.
• Deep mastery of Python and modern data/software engineering practices.
• Proven expertise with cloud‑native data architectures (GCP/BigQuery, AWS, or Azure), distributed computing, e