• You are the DRI for everything between raw ingestion and the clean data layer. • You own the modelling strategy and are trusted to push back when a request would compromise what we've built. • You'll audit what we have, cut what we don't need, and rebuild the rest into something clean, traceable, and maintainable. • You'll design and own our approach to data quality: what we test, how we test it, and what happens when something breaks. • You'll own the efficiency of our query and storage footprint, refactoring models and materialisation strategies to reduce unnecessary spend. • You'll build a robust event data model that gives us meaningful observability across our full product suite.

We're looking for a Senior Data Analytics Engineer to join our passionate and diverse Data Team. Treatwell is an organisation built on data, and we're just getting started. In this role, you'll be instrumental in shaping our future by ensuring our data models and analytical capabilities keep pace with the rapid growth of our business. As part of the Data Domain Team, you'll take end-to-end ownership of data products that empower analysts, product managers, and business stakeholders with meaningful insights. You'll work closely with teams across the business, translating their needs into reliable, well-structured data assets. You'll bring strong expertise in SQL, Python, and data model design to deliver the right data in the best format through self-serve and Machine Learning-enabled tools. We work with open-source platforms including DBT, Airbyte, Docker, GitLab, SageMaker, and Airflow. Our services run on AWS, including Redshift, ECS, Lambda, Cloudwatch, S3, EMR, and EC2, alongside third-party tools like Fivetran, Monte Carlo, Looker, JIRA, and Slack. We're also at an exciting point in our data journey with plans to modernise our data stack and transition to a Lakehouse architecture. This is a great opportunity to help shape the direction of how we store, model, and access data at Treatwell. You will be responsible for: - Collaborating with your data peers and business teams to understand their needs and build data products that surface performance insights and drive action - Modelling core data assets using SQL, DBT, Python and LookML - Supporting the development of Machine Learning models using Python and AWS SageMaker - Contributing to the strategy and design of data models and the data warehouse - Supporting the discovery and integration of new data sources (OLTP, APIs, S3) - Empowering analysts and business users through conversational analytics, self-serve tooling, education, and documentation - Defining and managing data quality, documentation, observability, and governance of core data models - Managing data exposures in Looker, ensuring smooth and reliable delivery of data to the business - Automating repetitive analyses and tasks wherever possible - Investigating and proposing solutions for data warehouse issues arising from daily query processing and end-user needs - Fostering a data-driven culture across the organisation

We're looking for a Senior Data Analytics Engineer to join our passionate and diverse Data Team. Treatwell is an organisation built on data, and we're just getting started. In this role, you'll be instrumental in shaping our future by ensuring our data models and analytical capabilities keep pace with the rapid growth of our business. As part of the Data Domain Team, you'll take end-to-end ownership of data products that empower analysts, product managers, and business stakeholders with meaningful insights. You'll work closely with teams across the business, translating their needs into reliable, well-structured data assets. You'll bring strong expertise in SQL, Python, and data model design to deliver the right data in the best format through self-serve and Machine Learning-enabled tools. We work with open-source platforms including DBT, Airbyte, Docker, GitLab, SageMaker, and Airflow. Our services run on AWS, including Redshift, ECS, Lambda, Cloudwatch, S3, EMR, and EC2, alongside third-party tools like Fivetran, Monte Carlo, Looker, JIRA, and Slack. We're also at an exciting point in our data journey with plans to modernise our data stack and transition to a Lakehouse architecture. This is a great opportunity to help shape the direction of how we store, model, and access data at Treatwell. You will be responsible for: - Collaborating with your data peers and business teams to understand their needs and build data products that surface performance insights and drive action - Modelling core data assets using SQL, DBT, Python and LookML - Supporting the development of Machine Learning models using Python and AWS SageMaker - Contributing to the strategy and design of data models and the data warehouse - Supporting the discovery and integration of new data sources (OLTP, APIs, S3) - Empowering analysts and business users through conversational analytics, self-serve tooling, education, and documentation - Defining and managing data quality, documentation, observability, and governance of core data models - Managing data exposures in Looker, ensuring smooth and reliable delivery of data to the business - Automating repetitive analyses and tasks wherever possible - Investigating and proposing solutions for data warehouse issues arising from daily query processing and end-user needs - Fostering a data-driven culture across the organisation

Posting Title Graduate Summer Intern – HPC Operational Analytics. Location Remote. Position Type Intern (Fixed Term). Hours Per Week 40. Working at NLR Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth. At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being. Job Description The Advanced Computing program at NLR has an opening for a graduate student researcher in High-Performance Computing (HPC) Operational Analytics. The researcher will assist in building the data foundation and AI-driven intelligence infrastructure for the facility, focusing on optimizing the operations of the Kestrel supercomputer. We are looking for a rigorous, motivated data scientist/engineer with a strong technical background in Python, machine learning, and systems architecture. The successful candidate will collaborate with NLR research scientists to analyze diverse facility telemetry and help build automated, agentic workflows to optimize supercomputing operations and workload scheduling. Responsibilities include: - Develop scalable Python pipelines to ingest and analyze diverse HPC telemetry - Build and evaluate machine learning models to characterize complex HPC workloads - Assist in developing automated, agentic AI workflows - Process and package operational data - Write robust, test-driven code and document data schemas within a collaborative Git repository. . Basic Qualifications Minimum of a 3.0 cumulative grade point average. Undergraduate: Must be enrolled as a full-time student in a bachelor’s degree program from an accredited institution. Post Undergraduate: Earned a bachelor’s degree within the past 12 months. Eligible for an internship period of up to one year. Graduate: Must be enrolled as a full-time student in a master’s degree program from an accredited institution. Post Graduate: Earned a master’s degree within the past 12 months. Eligible for an internship period of up to one year. Graduate + PhD: Completed master’s degree and enrolled as PhD student from an accredited institution. Please Note: • Applicants are responsible for uploading official or unofficial school transcripts, as part of the application process. • If selected for position, a letter of recommendation will be required as part of the hiring process. • Must meet educational requirements prior to employment start date. * Must meet educational requirements prior to employment start date. Additional Required Qualifications - Proficient in Python, specifically the data science and analytics stack - Comfortable operating in a Linux command-line environment. - Software engineering fundamentals, including Git and unit testing. Preferred Qualifications - Experience running code on HPC systems or using workload managers (e.g., Slurm). - Experience handling complex, large-scale data formats (time-series telemetry, system logs, or text-based data). - Familiarity with integrating Large Language Model (LLM) APIs into software workflows or building agentic systems. - Basic understanding of supercomputing architecture or facility operations. . Job Application Submission Window The anticipated closing window for application submission is up to 30 days and may be extended as needed. Annual Salary Range (based on full-time 40 hours per week) Job Profile: / Annual Salary Range: $44,500 - $71,200 NLR takes into consideration a candidate’s education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee’s salary history will not be used in compensation decisions. Benefits Summary Benefits include medical, dental, and vision insurance; 403(b) Employee Savings Plan with employer match*; and sick leave (where required by law). NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement. Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits. * Based on eligibility rules Badging Requirement NLR is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation. Intern assignments extending beyond six months will be subject to this requirement. Drug Free Workplace NLR is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug. If you are offered employment at NLR, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn. Submission Guidelines Please note that in order to be considered an applicant for any position at NLR you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application. . Equal Opportunity Employer All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws. Reasonable Accommodations E-Verify www.dhs.gov/E-Verify For information about right to work, click here for English or here for Spanish. E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.