Senior Staff Data Engineer — Scale Data Platform HealthTech

SmithRx; Austin (TX); On-site; USD 179,000 - 210,000; Full time

Benefits offered by this job

Medical benefits

Pharmacy benefits

Dental

Vision

Life Insurance

401(k) Retirement Savings Program

Discretionary Paid Time Off

12 Paid Company Holidays

Wellness Benefits

Commuter Benefits

Paid Parental Leave

Job summary

SmithRx is a rapidly growing Health-Tech company building a next-generation drug acquisition platform. We transform data streams to insights for PBM challenges, empowering analytics and ML teams to price drugs transparently.

The Data Engineering team designs, implements, and maintains distributed systems to collect, govern, and optimize pharmaceutical data using Airflow, DBT, Snowflake, and Python in a fast-paced environment.

Qualifications

• 8+ years of data engineering experience or 12+ years with a CS undergrad.
• Experience with data modeling and data warehouses (Snowflake).
• Strong PySpark, SQL and Python skills; OO languages a plus.
• Hands-on with ETL tools and frameworks (Airflow, dbt).
• Proven track record in cross-functional collaboration.

Responsibilities

• Define the long-term data engineering strategy guided by company priorities.
• Design pipelines and API boundaries; simplify infrastructure to lower maintenance costs.
• Make high-impact technical choices and review designs to identify risks.
• Improve developer efficiency with engineering-wide quality practices.

Skills

Data modeling

Snowflake

PySpark

SQL

Python

Big data workflows

Leadership

Executive communication

Education

Advanced degree in CS/related field

Undergraduate degree in CS/IT or related field

Tools

Apache Spark

Apache Airflow

dbt

Looker

Superset

Job description

SmithRx is a rapidly growing Health-Tech company building a next-generation drug acquisition platform. We transform data streams to insights for PBM challenges, empowering analytics and ML teams to price drugs transparently.

The Data Engineering team designs, implements, and maintains distributed systems to collect, govern, and optimize pharmaceutical data using Airflow, DBT, Snowflake, and Python in a fast-paced environment.