Data Engineer

AP MAX INC
14hRemote

About The Position

At Allia Health, the umbrella organization for Southend Pharmacy, Brello Health, and Woven, we don’t just follow industry trends—we redefine them. Our mission is to commoditize anti-aging solutions, making them affordable and accessible to the average consumer—not just the wealthy. By offering customized and cost-effective wellness products that follow cost-containment models, we aim to improve people’s quality of life and meet them wherever they are on their health journey. The Data Engineer will support the growth and scaling of Allia Health Group’s data platform. This role focuses on building, maintaining, and improving data pipelines and data models that enable analytics, reporting, and AI initiatives. Working closely with Senior Data Engineers, AI, and Product teams, the Data Engineer will help ensure data is reliable, well-structured, and accessible across the organization.

Requirements

  • Ideal Degree(s): BSc or MSc in Computer Science, Data Engineering, Data Science, or a related field
  • 2+ years of experience in data engineering, analytics engineering, or a related role (or equivalent hands-on experience)
  • Strong SQL skills
  • Experience with at least one programming language (Python preferred)
  • Basic understanding of ETL/ELT processes and data modeling concepts
  • Familiarity with cloud data platforms (Google BigQuery preferred; AWS/Azure acceptable)
  • Ability to work collaboratively in cross-functional teams
  • Strong attention to detail and interest in data quality

Nice To Haves

  • Exposure to data orchestration or transformation tools (e.g., dbt, Airflow)
  • Experience with BI or analytics tools (Looker preferred)
  • Familiarity with Google Cloud Platform and modern data stacks
  • Interest in analytics, AI, or machine learning use cases

Responsibilities

  • Assist in designing, building, and maintaining ETL/ELT data pipelines
  • Support data ingestion from internal and external data sources
  • Help maintain and improve data warehouse structures and data models
  • Ensure data quality through validation, testing, and monitoring processes
  • Support analytics and BI use cases by preparing clean, well-documented datasets
  • Collaborate with senior engineers and stakeholders to understand data requirements
  • Contribute to documentation and continuous improvement of the data platform
  • Follow software engineering best practices including version control, testing, and CI/CD
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