Senior Data Engineer: Lead Scalable Pipelines & Governance

SmithRx

United States

Remote

USD 214,000 - 252,000

Full time

14 days+
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Benefits offered by this job

401(k) Retirement Savings Program
Discretionary Paid Time Off
Wellness Benefits
Paid Parental Leave

Job summary

SmithRx is seeking an experienced Data Engineer to shape the architecture of its PBM data platform. You will lead the design of scalable data pipelines, governance, and analytics enablement, collaborating with analytics and ML teams.

Expect high-impact work in a fast-growing health-tech company with a strong mission to transform healthcare costs. You will mentor engineers, define technical direction, and drive end-to-end data lifecycle initiatives across distributed systems, prioritizing data

Qualifications

  • 8+ years of industrial data engineering experience with an advanced degree or 12+ years with a relevant undergrad.
  • Strong mastery of data modeling, warehousing (Snowflake), and production-grade implementations.

Responsibilities

  • Define the long-term data engineering strategy guided by company priorities and best practices.
  • Design coherent pipelines across APIs; simplify infrastructure to reduce maintenance costs.
  • Drive engineering excellence: build-vs-buy decisions, framework selection, risk review.
  • Mentor engineers and communicate technical strategy to executives with clarity.

Skills

PySpark
SQL
Python
Airflow
dbt
Looker
Superset
Snowflake
Spark

Education

Advanced degree in CS/IT

Tools

Apache Spark
Airflow
dbt
Looker
Superset

Job description

SmithRx is seeking an experienced Data Engineer to shape the architecture of its PBM data platform. You will lead the design of scalable data pipelines, governance, and analytics enablement, collaborating with analytics and ML teams.

Expect high-impact work in a fast-growing health-tech company with a strong mission to transform healthcare costs. You will mentor engineers, define technical direction, and drive end-to-end data lifecycle initiatives across distributed systems, prioritizing data

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