Senior Data Analytics Engineer

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September 9

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Fullscript

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Healthcare Insurance • Wellness • SaaS

Fullscript is a comprehensive platform that facilitates whole person care for healthcare providers. It integrates industry-leading lab testing, high-quality supplements, and a suite of tools designed to enhance patient adherence and outcomes. Fullscript offers features like personalized patient plans, evidence-based templates, patient engagement tools, and seamless wholesale ordering of supplements. The platform also integrates with top EHR systems to streamline workflows for healthcare practitioners, making it easier for them to provide effective care. With Fullscript, patients can manage their health routines more conveniently, and providers can create personalized care plans with the support of clinical evidence and insights.

201 - 500 employees

Founded 2016

⚕️ Healthcare Insurance

🧘 Wellness

☁️ SaaS

💰 $240M Private Equity Round on 2021-11

📋 Description

• Work cross-functionally to help define, build, and deploy our Enterprise Data Warehouse to serve reporting and analytical needs across Fullscript. • Work with Fullscript’s engineering team and other business stakeholders to define and implement our Customer Data Platform (CDP), which uses data from a variety of sources to power decision making about customer acquisition and the customer journey. • Write data transformation code in ELT pipelines, and work with data delivery tools to ensure the data arrives where it is needed to support this decision making. • Mentor and provide technical guidance to junior members of the team, and provide guidance and influence to all practitioners of the Analytics Engineering craft throughout the company. • Ensure data models are properly tested and optimized for scalability and performance. • Create and maintain data documentation and definitions.

🎯 Requirements

• 5+ years in Data Analytics and/or Data Engineering, implementing ETL/ELT processes. • Strong proficiency in SQL. • Experience with dbt (data build tool) for implementing transformation stages. • Experience working with Cloud Data Warehouses such as Snowflake, BigQuery or Redshift. • Hands-on experience with data modeling, schema design, and optimization techniques. • Proven experience maintaining data transformation pipelines, ensuring data availability and quality, meeting SLAs, and communicating status to downstream consumers. • Deep understanding of data engineering best practices, including version control, testing, and CI/CD methodologies. • Ability to communicate complex technical concepts effectively to technical and non-technical stakeholders. • Learning mindset, with a keen interest in exploring new technologies and methodologies. • Bonus: Experience with a Customer Data Platform (CDP). • Bonus: Experience with ops practices and tools for automated deployment, CI pipeline definition, and infrastructure management. • Bonus: Previous experience in a leadership or mentorship role in a data engineering team. • Bonus: A cover letter explaining why analytics engineering is of special interest to you.

🏖️ Benefits

• Flexible PTO & competitive pay—rest fuels performance. • RRSP match & stock options—invest in your future. • Customizable benefits—flexible coverage, paramedical services, and an HSA. • Fullscript discounts—save on wellness products. • Continuous learning—training budget + company-wide initiatives. • Wherever You Work Well—hybrid and remote flexibility.