Posting record
Open 11+ days
- Doctronic's site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Doctronic, so its true age is longer.
Last checked Nov 1, 2026.
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Upload your resumeWhat the posting discloses
- Pay
- $200k to $275k a year USD
Base salary range: $200,000 to $275,000 annually, depending on experience, plus meaningful equity (quoted from the posting)
Not stated: Real vacancy, AI screening.
Why these three
Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.
Skills mentioned
About the role
The Role
You will be Doctronic's first dedicated data engineer, and you will own the plumbing end to end: how data moves from our production systems into our lakehouse and warehouse, how it gets transformed into trusted, documented tables, and who can access what.
This role serves every team in the company: AI engineering, product, finance, partnerships, and data to name a few.
What You'll Do
- Build reliable, monitored CDC pipelines from our production databases (MariaDB, PostgreSQL, MongoDB) into our S3 + Iceberg lake and Snowflake
- Stand up a transformation layer (e.g. dbt) on Snowflake so core business metrics (visits, bookings, revenue, retention) come from tested, version-controlled models
- Select and implement an orchestration tool so pipelines and dashboard refreshes run automatically, with alerting when they break
- Design and enforce the access control model for patient data: row/column-level PHI restrictions, HIPAA Safe Harbor compliance, anonymization pipelines, and account deletion workflows
- Establish a single governed copy of production data that analytics, finance, and the AI team all read from
- Support the AI team's data needs for model training
- Design and build a best-practice warehouse architecture with clean raw, transformed, and business-ready layers powering our executive dashboards
What We're Looking For
- 5+ years of data engineering experience, including ownership of production data platforms end to end
- Strong SQL and Python, with experience building and operating ELT/CDC pipelines (Fivetran, Airbyte, or similar)
- Hands-on experience with a modern lakehouse/warehouse stack: S3, Apache Iceberg, a catalog layer, and Snowflake or an equivalent warehouse
- Experience with transformation frameworks (dbt or similar) and orchestration tools (Airflow, Dagster, Glue workflows, or similar)
- Solid AWS fundamentals: IAM, Lambda, Kinesis, Glue
- A pragmatic, reliability-first mindset
- Comfort operating with high autonomy and minimal specs in a flat, engineering-first organization
- Strong communication skills; you'll work directly with product, marketing, finance, and AI stakeholders
Nice to Have
- Experience with HIPAA/PHI data governance, anonymization, or healthcare data
- Experience with event/behavioral data pipelines (ClickHouse, GTM/server-side tracking, CDPs)
- Familiarity with ML data workflows: feature pipelines, training datasets, notebook environments (SageMaker, Databricks, Jupyter)
- Experience with BI tooling (Metabase or similar) and semantic/metrics layers
- Prior experience as the first or only data engineer at a startup
Compensation & Benefits
- Base salary range: $200,000 to $275,000 annually, depending on experience, plus meaningful equity
- Parental Leave: 12 weeks fully paid parental leave for all parents, regardless of gender or path to parenthood — no distinction between birthing and non-birthing parent
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