Adoreal
Adoreal
51 – 200 Employees
ConsultingHealthcareLogistics
Adoreal is a healthcare and beauty technology company focused on cosmetic and reconstructive surgery and aesthetic procedures. Its integrated platform helps people explore treatment options, assess their needs, and plan personalized care through tools such as 3D simulation and tailored evaluations. By bringing information and decision-support resources together, Adoreal aims to make the treatment journey more transparent, informed, and convenient.

Senior Data Engineer at Adoreal — Remote, United States

Lead warehouse architecture, semantic modeling, and AI-enabled data pipelines for Adoreal’s products serving plastic surgery and aesthetic medicine practices.

Description

  • Own the target architecture for the data warehouse and curated layer, recording design decisions and guiding its long-term direction.
  • Create a semantic layer that centralizes metric definitions, formulas, and rationale.
  • Define standards for naming, labels, lineage, enumerated values, and the historical tracking of business rules.
  • Develop a configuration model for practice-specific business rules.
  • Collaborate with data engineers daily and provide regular code and work reviews.
  • Build the gold layer and foundational reporting library for new practices, including patient journeys, capacity, and growth.
  • Expand infrastructure as code and continuous integration across the warehouse and pipelines, with schema-drift testing.
  • Transform unstructured clinical records, including HTML and PDF journals, notes, and submitted forms, into usable data.
  • Automate migration profiling, delta reconciliation, data-quality validation, and report provisioning.
  • Use AI in data pipelines for enrichment, anomaly detection, metadata creation, data dictionaries, and enumerated-value catalogs.
  • Prepare the warehouse for safe, effective AI use through cataloging, semantic querying, evaluation sets, and governance for patient-data tools.
  • Create repeatable migration processes covering profiling, delta matching, schema mapping, record matching, and rejected-record reporting.
  • Work with engineering on platform changes and formal contracts for warehouse-platform updates.
  • Partner with product and commercial leaders to establish meaningful business metrics.

Requirements

  • At least eight years of data-engineering experience, including end-to-end ownership of warehouse or lakehouse architecture from ingestion through the curated layer used by stakeholders.
  • Advanced SQL and Python skills, with production experience using a modern cloud data warehouse.
  • Experience with Redshift, Snowflake, BigQuery, or Databricks.
  • Practical experience building a semantic or metrics layer with dbt or a comparable tool.
  • Production experience with orchestration and infrastructure as code on AWS, such as Airflow and Terraform.
  • Experience designing and operating dimensional or Data Vault models in production.
  • Experience implementing data-quality tests and observability with dbt tests, Great Expectations, or an equivalent solution.
  • Regular use of coding agents and AI tools in day-to-day engineering work.
  • Experience applying AI within a data platform, such as LLM-based unstructured-record classification, entity matching, anomaly detection, or natural-language querying over a semantic layer, supported by an evaluation set.
  • Experience handling regulated data, including healthcare or financial information.
  • Current, valid authorization to work in the country where you submit your application.
  • Adoreal does not provide visa sponsorship for this role.

Benefits

  • Healthcare coverage for employees and their families.
  • 401(k) plan.
  • Paid time off.
  • Paid company holidays.
  • Opportunities to participate in company equity.
  • Fully remote work with flexible scheduling.
  • Collaborative, high-performing team culture.
  • Opportunities for advancement and professional growth.
  • Disability accommodations are available throughout the recruitment process.

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