ABOUT TRUDATARX
TruDataRx, Inc. uses objective clinical data to help clients improve the clinical efficacy and reduce the costs of pharmacy benefits for its members. We are independent from all players in the pharmaceutical manufacturing and distribution industries, enabling us to best serve our clients. We value the following characteristics in our team members:
- Outward Mindset – foundation of our culture, which influences the right behaviors, that leads to results
- Entrepreneurial – the ability to get things done with resources you don’t control
- Humility – deep comfort in knowing when you don’t know and asking questions
- Collaboration – we always give benefit of doubt that each person has something to contribute
POSITION SUMMARY:
We are seeking an experienced Data Engineer to architect, build, and maintain our next-generation data pipelines. You will be the technical subject matter expert on our Modern Data Stack, primarily utilizing Snowflake and dbt.
You will be responsible for defining best practices, conducting code reviews, and actively nurturing the growth of junior engineers. You will act as a bridge between raw data and actionable analytics, ensuring our analysts and data scientists have clean, reliable, and timely data.
ESSENTIAL FUNCTIONS
- ELT Architecture: Design and build robust, scalable ELT pipelines to ingest data from various sources (APIs, production databases, third-party tools) into Snowflake.
- Data Transformation (dbt): Own the dbt project structure. specific responsibilities include:
- Developing complex SQL-based data models (incremental models, snapshots).
- Writing Jinja macros to keep code DRY (Don't Repeat Yourself).
- Implementing data quality tests (schema tests, custom data tests).
- Snowflake Optimization: Manage the Snowflake environment to ensure cost-efficiency and performance. This includes warehouse sizing, clustering strategies, and utilizing features like Snowpipe and Zero-Copy Cloning.
- Data Quality & Governance: Champion data integrity. Implement observability tools and alerts to catch pipeline failures or data anomalies before they reach the business users.
- Mentorship: Act as a technical lead for junior engineers, conducting code reviews, and establishing best practices for SQL and version control.
- Collaboration: Translate business requirements from Product and Analytics teams into technical specifications and data models