Senior Data Engineer

. Own the target architecture for the warehouse and curated layer, document design decisions, and determine future architecture direction .

Posted 9/26/2026full-timeRemote • United StatesSenior💰 $110,000 - $135,000 per yearWebsite

Tools & technologies

AirflowAmazon RedshiftAWSBigQueryCloudPythonSQLTerraformVault

Key responsibilities & impact

Own the target architecture for the warehouse and curated layer, document design decisions, and determine future architecture direction
Design a semantic layer as a single metric repository with definitions, formulas, and reasoning
Establish standards for naming, labeling, lineage, enumerated values, and business-rule history
Build a configuration model for practice-specific business rules
Pair with data engineers daily and review work
Build the gold layer and baseline report library for new practices, covering patient journey, practice capacity, and growth
Extend infrastructure as code and CI across the warehouse and pipelines, including schema-drift tests
Structure unstructured clinical records, including HTML and PDF journals, notes, and form submissions
Automate migration profiling, delta reconciliation, data quality checks, and report provisioning
Apply AI in pipelines for enrichment, anomaly detection, metadata generation, data dictionaries, and enum catalogs
Make the warehouse safe and useful for AI through cataloging, semantic querying, evaluation sets, and patient-data tool governance
Develop repeatable migrations with profiling, delta matching, schema mapping, record matching, and rejected-record reporting
Partner with engineering on platform changes and warehouse-platform change contracts
Work with product and commercial leadership to define meaningful business metrics

What you’ll need

8+ years in data engineering, including end to end ownership of a warehouse or lakehouse architecture, from ingestion through to the curated layer that people actually query
Deep SQL and Python, with production experience on a modern cloud warehouse
Experience with Redshift, Snowflake, BigQuery, or Databricks
Hands-on experience building a semantic or metrics layer using dbt or an equivalent tool
Production experience with orchestration and infrastructure as code on AWS, such as Airflow and Terraform
Experience designing and maintaining dimensional or Data Vault models in production
Data quality testing and observability using dbt tests, Great Expectations, or an equivalent
Daily use of coding agents and AI tooling in own work
AI applied inside a data platform, such as LLM classification of unstructured records, entity matching, anomaly detection, or natural language querying over a semantic layer, with an evaluation set
Experience with regulated data, such as healthcare or financial data
Must have current and valid authorization to work in the country where applying
Adoreal is not offering visa sponsorship for this position

Comp & perks