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Senior Data / Analytics Engineer

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Salary

$150,000 - $150,000

Location

Remote

Posted

Today

This is a foundational role within the Tech & Data organization, reporting directly to the Director of Tech & Data. You will help modernize and scale our data architecture across marketing, operations, finance, sales, and clinical systems while maintaining continuity for existing reporting, analytics, and business operations. This role is ideal for someone who thrives in high-growth environments and enjoys bringing structure, reliability, governance, and scalability to complex and evolving data ecosystems. You will play a central role in rebuilding and organizing our data foundation, establishing standards and architecture patterns, improving transformation and modeling practices, and helping create a modern healthcare data platform designed for long-term scale and AI-enabled workflows. This is not a pure backend engineering role. We are looking for someone who combines strong analytics engineering and warehouse architecture experience with practical business judgment and modern data stack expertise.

What you'll own

Data architecture & modernization

  • Help design and implement a scalable modern data architecture within Google BigQuery
  • Rebuild and organize fragmented data structures into standardized, maintainable models
  • Establish naming conventions, modeling standards, lineage, and governance frameworks
  • Help separate and structure sensitive vs non-sensitive data appropriately in a HIPAA-conscious environment
  • Partner with leadership to define long-term warehouse and transformation architecture strategy
  • Improve scalability and maintainability without disrupting existing business operations

Analytics engineering & data modeling

  • Own and expand our dbt transformation layer and modeling practices
  • Build clean, scalable transformation pipelines and business logic layers
  • Create reliable curated datasets for analytics, reporting, operational workflows, and AI initiatives
  • Standardize KPI logic and reduce duplicated transformation logic across systems
  • Develop testing, QA, and documentation standards for data models and pipelines
  • Improve data quality, observability, and reliability across the warehouse

Data pipelines & platform operations

  • Build, maintain, and optimize ingestion and transformation pipelines across internal and third-party systems
  • Work across platforms including:
  • Google BigQuery
  • dbt
  • Fivetran
  • Portable
  • Improvado
  • HubSpot
  • Tableau
  • Google Cloud Platform
  • Troubleshoot pipeline failures, schema drift, integration issues, and data discrepancies
  • Improve monitoring, documentation, and operational stability across the data stack

AI-ready data infrastructure

  • Help build structured, reliable, AI-ready datasets and systems
  • Partner with Tech & Data leadership on long-term AI infrastructure readiness
  • Support future AI-enabled workflows, automation initiatives, and operational tooling
  • Contribute to scalable data design practices that support evolving AI use cases across the business

Cross-functional collaboration

  • Partner closely with analysts, marketing, operations, finance, and technology stakeholders
  • Support analysts by improving foundational data models and reducing engineering burden on analytics resources
  • Collaborate with IT and leadership on governance, access, and long-term platform maturity
  • Participate in architectural planning and technical roadmap discussions

Required experience

  • 5-8+ years in analytics engineering, data engineering, or modern data stack environments
  • Strong expertise in SQL and warehouse-based data transformation workflows
  • Hands-on experience with dbt and modern ETL workflows
  • Deep experience working within Google BigQuery or comparable cloud data warehouses
  • Proficiency with SFTP-based file transfer workflows, including key-based authentication, scheduled transfers, and error handling
  • Experience designing scalable data models and transformation layers
  • Experience working with complex operational and business systems data
  • Strong understanding of data governance, documentation, testing, and QA practices
  • Experience building and maintaining production-grade data pipelines
  • Strong systems thinking and architectural judgment
  • Ability to balance long-term architecture improvements with short-term operational stability

Preferred experience

  • Experience with:
  • Fivetran
  • Portable
  • Improvado
  • Tableau
  • HubSpot
  • Google Cloud Platform
  • Experience in healthcare or HIPAA-conscious environments
  • Experience supporting marketing, operational, or revenue-focused analytics ecosystems
  • Familiarity with AI-enabled data workflows and AI-ready platform design
  • Experience helping mature or rebuild fragmented data environments
  • Familiarity with Jira and collaborative technical project management workflows

What success looks like

  • Establish scalable architecture and modeling standards across the warehouse
  • Mature and expand the dbt transformation layer
  • Improve documentation, lineage, governance, and data reliability
  • Organize fragmented datasets into scalable, maintainable structures
  • Improve separation and governance of sensitive vs non-sensitive data
  • Reduce operational friction and engineering burden across the analytics ecosystem
  • Build a more scalable and AI-ready data foundation for the future growth of the organization

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