About our teams: Tempus is executing on the mission to create the world’s largest, integrated dataset of molecular and clinical data. At Tempus, products are owned and developed by small, autonomous teams composed of developers, designers, data scientists, and product managers. You and your team set the goals, build the software, deploy the code, and contribute to a growing software platform that will make a lasting impact in the field of cancer research and treatment.
Tempus builds software as nimble as our teams. Our modern tech stack allows our teams to iterate rapidly and lead our industry in innovation. Our decentralized, microservice architecture and emphasis on automation allow us to deliver advanced solutions with confidence, and at scale.
What You’ll Do
- Design, develop, and optimize data structures, ETL/ELT solutions, stored procedures, and functions using SQL and modern, cloud-based ETL/ELT technologies.
- Work with team architects and internal stakeholders across the company in areas such as data science, clinical and molecular SMEs, and source system data producers to refine business requirements during development.
- Evaluate completeness of source system data by performing a profiling analysis.
- Deploy code with established CI/CD change management guidelines.
- Monitor performance of production processes and recommend areas for improvement.
- Triage issues reported by users in production systems.
- Analyze existing SQL queries for performance improvement opportunities.
- Implement solutions to proactively monitor data quality with traceability to source systems.
- Maintain data warehouse ecosystem documentation such as ER Diagrams, data dictionaries, process descriptions, data catalog, etc. according to team standards.
Why we’re looking for you:
- Domain knowledge in healthcare or genomics.
- Knowledge of dimensional and relational database modeling concepts such as referential integrity, normalization, etc.
- Ability to translate business requirements into SQL code.
- Ability to adapt quickly in a rapidly changing environment while effectively managing multiple projects and priorities simultaneously.
- Exceptional SQL skills in an enterprise data warehouse environment.
- Experience with ETL/ELT and BI architectures, concepts and frameworks.
- Knowledge of data management best practices like incremental vs full loads, how to handle deleted data in source systems, insert-only vs merge architecture, etc.
- Background working with high volume and high velocity data warehouses.
- Emphasis on data quality, unit testing, and creating testing frameworks for reliable data.
- Comfortable working with stakeholders and SMEs across the company.
- Enjoys a fast-paced environment with a variety of small projects and bigger initiatives.
- Flexible to changing priorities.
Bonus points for:
- Experience with AWS or GCP architecture
- Experience working with clinical and/or genomic data
- Experience writing and debugging Python (SQL is required)
- Familiarity with modern ELT tools such as DBT
- Familiarity working within containerized environments