Senior Azure Databricks Engineer

Pacific Northwest National Laboratory

About The Position

At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget. Our directorates related to Mission Support & Operations include Office of General Counsel, Business Services, Communications and External Engagement, Operational Systems, Communications and Information Technology, and Performance Management. At PNNL, our Computing and Information Technology organization is redefining how we work and innovate by reimagining the digital workplace. We empower research and streamline operations—making both faster, smarter, and more efficient—so our professionals can tackle some of the world's toughest challenges in science, energy, and national security. Our experts in AI, cybersecurity, design, and engineering work side by side, using real-time insights and human-centered design to break down barriers. Ready to make your mark on tomorrow? Come work with us. In support of PNNL's mission, Digital Platforms collaborates closely with our business and technology partners to build and maintain innovative software solutions and robust data and analytics capabilities. We aim to be a strategic partner in delivering cutting-edge enterprise solutions that drive innovation and improve the way our staff work across the PNNL digital workplace. Our forward-thinking, agile teams leverage cloud technologies, DevSecOps, and AI to modernize existing platforms and assist in the creation of novel solutions. By integrating commercial products, custom-developed and low-code solutions, we ensure our digital platforms are ready for the challenges and opportunities of tomorrow.

Requirements

PhD and 3 years of relevant experience -OR- MS/MA or higher and 5 years of relevant experience -OR- BS/BA and 7 years of relevant experience -OR- AA and 16 years of relevant experience -OR- HS/GED and 18 years of relevant experience
Qualifying software development experience in designing, architecting, programming, deploying, and automating software solutions in support of scientific research or consumer digital product development may be counted

Nice To Haves

7+ years of professional data engineering or platform engineering experience, with 3–5+ years focused on cloud data platforms.
5+ years of experience operating production Azure Databricks, including Delta Lake, SQL, notebooks, Jobs/Workflows, and cluster management.
Production experience (3-5+ years) designing and operating ingestion-to-gold pipelines (medallion architecture) for ERP or other complex transactional sources.
Experience with Azure Data Factory and/or Fabric Data Pipelines for orchestration and integration.
Familiarity with core Azure services: ADLS Gen2, Key Vault, Azure DevOps or GitHub.
Strong proficiency in Python and SQL in a Spark/Databricks environment.
Experience implementing Databricks Asset Bundles (DAB) or equivalent for CI/CD and standardizing deployment workflows.
Experience using GenAI / LLM-based tools (e.g., GitHub Copilot, Azure OpenAI, Databricks Genie, or similar) to accelerate and automate engineering tasks such as code generation, test creation, documentation, and troubleshooting.
Exposure to agentic AI / AI agents (e.g., orchestrating multi-step AI workflows for data quality checks, pipeline monitoring, or support automation) is a plus.

Responsibilities

Lead the design, build, and operation of our data lakehouse that powers analytics and reporting across PNNL Enterprise Systems.
Deliver governed, performant, and reliable data products—especially for ERP and other enterprise —and enabling self-service analytics with Power BI and AI/ML.
Design and evolve a Databricks‑based architecture that moves data with confidence from source systems to curated gold tables.
Build robust pipelines that transform raw data into analytics‑ready assets for Power BI and AI/ML, balancing pragmatic MVP delivery with a future‑focused architecture.
Lead modernization from legacy data warehouses and ETL tools into Azure Databricks—refactoring brittle jobs into scalable patterns.
Shape CI/CD for Databricks (e.g., DAB, Azure DevOps, GitHub Actions) and standardize deployment practices across environments.
Configure and operate workspaces, clusters, jobs, and workflows; tune for performance and reliability; and embed data quality, monitoring, and observability to keep critical pipelines healthy.
Implement role‑based access controls, data masking, and fine‑grained models with Unity Catalog to enable secure, compliant data sharing and ensure proper classification, lineage, and auditability.
Guide engineers and analysts in adopting lakehouse best practices and modern data engineering standards—coding, testing, version control, and documentation.
Stay current with Azure and Databricks capabilities, recommending and piloting features like Delta Live Tables and Unity Catalog enhancements to build a secure, reliable, and future‑ready data platform that accelerates science and mission delivery.

Benefits

Employees and their families are offered medical insurance, dental insurance, vision insurance, robust telehealth care options, several mental health benefits, free wellness coaching, health savings account, flexible spending accounts, basic life insurance, disability insurance, employee assistance program, business travel insurance, tuition assistance, relocation, backup childcare, legal benefits, supplemental parental bonding leave, surrogacy and adoption assistance, and fertility support.
Employees are automatically enrolled in our company-funded pension plan and may enroll in our 401 (k) savings plan with company match.
Employees may accrue up to 120 vacation hours per year and may receive ten paid holidays per year.

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