SmithRx

Senior Staff Data Engineer

SmithRx

full-time

Posted on:

Location Type: Remote

Location: United States

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Job Level

Senior

Tech Stack

AirflowApacheDistributed SystemsETLGoJavaPySparkPythonScalaSparkSQL

About the role

  • Define Technical Vision: Define the long-term data engineering strategy, factoring in company-wide priorities, customer needs, and system limitations.
  • Design Ecosystems: Create coherent designs across multiple pipelines and API boundaries. Reduce complex concepts to foundational components and simplify infrastructure to lower maintenance costs.
  • Drive Engineering Excellence: Make high-impact technical choices—including "build vs. buy" and framework selections—and provide clear rationale to rally the team. Review cross-team designs to preemptively identify and resolve technical risks before they jeopardize projects.
  • Improve Developer Efficiency: Implement solutions that measurably improve developer efficiency (e.g., cycle time, ramp-up time) and establish engineering-wide quality and best practices.
  • Deliver at Scale: Roll out major features and systems reliably, ensuring appropriate monitoring, failure domain characterization, and clear success metrics are established post-launch.
  • Align with Business Goals: Leverage a deep understanding of SmithRx’s business strategy to identify group-wide opportunities. Proactively refocus team efforts when projects are off-course or not moving the needle for the business.
  • Manage Data Quality & Governance: Enforce data governance policies (PII/PHI protection, security, compliance) and implement data quality principles to raise the bar for the reliability of data shared internally and externally.
  • Influence Cross-Functionally: Influence the roadmaps of other SmithRx teams. Act thoughtfully and decisively in critical situations, seeking diverse perspectives but ultimately leading decision-making (disagree and commit) to move priorities forward.
  • Mentor and Develop: Serve as a role model and coach for SDE2/SDE3 engineers, taking into account their unique skills and providing constructive feedback to maximize their impact.
  • Executive Communication: Develop focused messaging and effectively present technical strategies and business cases at the executive level.
  • Champion Organizational Change: Break down silos, build deep cross-functional relationships, and create excitement to drive the adoption of new technologies or processes across the organization.

Requirements

  • 8+ years of years of industrial experience in data engineering with an advanced degree or 12+ years with an undergraduate degree in Computer Science, Information Technology, or a related field. (Start-up and healthcare experience is highly desirable).
  • Demonstrated mastery of data modeling concepts, database design principles, and data warehouse technologies (e.g., Snowflake) through production-grade implementations.
  • Strong skills in PySpark, SQL, and Python. Experience in modern object-oriented or compiled languages such as C#/C++, Go, Java, or Scala.
  • Hands-on experience with leading ETL tools and frameworks (e.g., Apache Spark, Apache Airflow, dbt, Looker, Superset).
  • In-depth experience managing the entire data lifecycle, with direct responsibility for the development, implementation, and production release of complex data processing solutions utilizing distributed systems.
  • A proven track record of making decisions optimized for the wider engineering organization rather than locally optimal outcomes, especially in environments with significant ambiguity.
Benefits
  • Highly competitive wellness benefits including Medical, Pharmacy, Dental, Vision, and Life Insurance and AD&D Insurance
  • Flexible Spending Benefits
  • 401(k) Retirement Savings Program
  • Short-term and long-term disability
  • Discretionary Paid Time Off
  • 12 Paid Company Holidays
  • Wellness Benefits
  • Commuter Benefits
  • Paid Parental Leave benefits
  • Employee Assistance Program (EAP)
  • Well-stocked kitchen in office locations
  • Professional development and training opportunities
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
data engineeringdata modelingdatabase designdata warehouse technologiesPySparkSQLPythonETL toolsApache SparkApache Airflow
Soft Skills
influencementoringexecutive communicationcross-functional collaborationdecision-makingproblem-solvingleadershipstrategic thinkingadaptabilitycoaching