TrialSpark is a digital health company that accelerates the discovery of new treatments for patients by reimagining the clinical trial process.
Today, clinical trials are deeply inefficient. A single clinical trial can cost more than 100 million dollars and less than 10% of clinical trials are completed on time. Our mission is to bring treatments to patients faster by addressing these inefficiencies.
As an Analytics Engineer, you'll be the chief steward of our analytical data infrastructure. An analyst at heart, you will build reliable data models, surface key company metrics, and develop tools that streamline data discovery and knowledge sharing. You'll work closely with our Platform engineers, data scientists and data analysts to create a data architecture that ensures the right information is available and accessible to all stakeholders throughout the organization.
At TrialSpark we pride ourselves on being data-driven and our decision making rests on our ability to leverage data in the best ways possible. As such, the Analytics Engineer plays a central role to how we make those decisions in as fast and reliable a way as possible. A good candidate will be able to balance the structure required to curate a highly robust and high fidelity data warehouse, while understanding that as a start-up, you need to be nimble, iterative and always looking to learn. In addition to running the day-to-day, you’ll be asked to look for ways to improve our processes as the business scales.
Duties include, but are not limited to:
- Build and maintain the analytics layer of our team’s data environment to make data standardized and easily accessible (we use dbt as our data transformation tool)
- Maintaining and improving our Looker model to ensure that stakeholders can access the data they need in a clear and reliable way
- Integrating third party data sources as we add marketing channels, data partners and other vendors
- Working closely with Product and Engineering to ensure upstream product model changes integrate well with our data model; and when it doesn’t build the necessary capabilities to adjust
- Supporting our CCD and OMOP model transformations
- Managing user roles and permissions for Redshift and Looker
- When needed, performing stakeholder related work, such as dashboards or analysis
- Integrating and productionizing analyst and data science models as needed
- Build data expertise, best practices and own data quality for all analytical data needs
- Define and manage SLA for all data sets in allocated areas of ownership
- 2-4 years of relevant analytical experience
- BS/BA in a quantitative degree
- Experience building analytical data models
- Proficient in SQL
- Proficient in LookML
- Experience with Python
- Experience with dbt a plus
- Strong communicator; experience working with non-technical stakeholders a plus
- You are passionate about our mission. You are excited about building the perfect team to bring medical treatments to patients faster.
- You are organized, persistent and empathetic. You consistently follow-up on tasks and aren’t afraid to track down people to help solve problems.