UL Research Institutes is hiring an onsite Data Engineer to help power Materials Discovery by building and operating data pipelines, data models, and data platforms that support analytics and machine learning. Based in Skokie, IL, this role combines deep technical ownership with collaboration across researchers and stakeholders, aligned to UL’s values of collaboration, respect, integrity, and beneficence.
What you’ll do
- Lead the architecture and technical implementation of MDRI’s data platforms, making trade-off decisions across scalability, performance, cost, security, and reliability.
- Set and enforce standards for data modeling, pipeline design, documentation, data quality, and reproducibility, including automated data quality checks and validation processes.
- Design, build, and evolve data architectures and ETL/ELT pipelines that ingest data from laboratory systems, databases, APIs, and external data providers, while ensuring accuracy, completeness, reproducibility, and timeliness.
- Evaluate and introduce modern data technologies and patterns such as cloud-native services, orchestration frameworks, and feature-ready datasets, while addressing scaling risks and performance bottlenecks.
- Integrate disparate data sources into unified, high-quality datasets and support data governance, security, and compliance with institutional standards and applicable regulations.
- Maintain comprehensive documentation, including contributions to data dictionaries and metadata repositories for long-term sustainability.
- Partner with researchers and stakeholders to define data and modeling approaches for research, operational, and business needs.
- Assess and justify modeling techniques, perform exploratory data analysis and feature engineering, and develop/train/evaluate machine learning and statistical models to establish feasibility, baselines, and data requirements.
- Document assumptions, inputs, outputs, limitations, and evaluation results, and hand off validated models, feature sets, and documentation for deployment and operationalization.
- Troubleshoot complex data and model issues across development and production environments.
- Perform other duties as assigned.
What you bring
- Demonstrated experience owning and evolving data platforms or systems end-to-end.
- Strong proficiency in SQL and Python, including data analysis and machine learning libraries such as pandas, NumPy, scikit-learn, PyTorch, and TensorFlow.
- Experience with cloud platforms including Azure, AWS, or Google Cloud and associated data and analytics services.
- Familiarity with infrastructure-as-code and containerization technologies such as Terraform, Docker, and Kubernetes.
- Experience with data integration, orchestration tools, and distributed processing frameworks such as Apache Spark, Azure Databricks, and Azure Data Factory.
- Solid understanding of machine learning fundamentals, feature engineering, evaluation techniques, and experiment reproducibility.
- Knowledge of data governance, security, privacy, and compliance best practices.
- Strong communication and problem-solving skills, including the ability to communicate effectively with technical and non-technical audiences.
Tools you’ll work with
SQL, Python, pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Azure, AWS, Google Cloud, Terraform, Docker, Kubernetes, Apache Spark, Azure Databricks, Azure Data Factory, ETL/ELT
Compensation and benefits
- Salary: USD 81,456 - 112,002 per year
- Bonus compensation eligibility
- Comprehensive medical, dental, vision, and life insurance plans
- 401k matching structure of up to 5% of eligible pay
- Additional 4% into your retirement saving fund after your first year of continuous employment
- Flexible working arrangements may be available depending on role
- Paid time off including vacation, holiday, sick, and volunteer days
Role requirements
- Education: Bachelor’s degree in Computer Science, Information Technology, Data Science, Engineering, or equivalent combination of education and experience
- Experience: Minimum 4 years of experience in a data engineering, analytics engineering, or closely related role
Job details: Onsite position in Skokie, Illinois. Pay type: Salary.
