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Data engineer job description template

General information, not legal advice. Last checked October 29, 2026.

By , tech recruiter at GuruLink in Winnipeg. Recruiting tech people since 2018. Updated .

How to use this

General information, not legal advice. Laws change. Check with an employment lawyer in your province before you post.

Put the pay in every posting.

In Ontario, from January 1, 2026, an employer with 25 or more employees must put a few things in every public job posting for work in Ontario. That means the expected pay or a pay range, a note if you use AI to screen, assess or select applicants, and whether the posting is for an existing vacancy (ESA ss. 8.2, 8.4, 8.5). A range can't be wider than $50,000 (O. Reg. 476/24, s. 4). The pay rule doesn't apply if the pay, or the top of the range, is over $200,000 a year (O. Reg. 476/24, s. 3). The ad and the application form also can't ask for Canadian experience (ESA s. 8.3).

BC needs the expected pay or range in every public posting, at any company size (Pay Transparency Act, s. 2). BC's guidance says "competitive wage" does not count (BC guidance).

Fill in the brackets. Delete the notes at the bottom before you post. Then run it through the Ontario 2026 checklist. Keep a copy of every version you post for 3 years (ESA s. 15(7.1)).

Name your real tools. Say how much data moves through the pipes. If the job has on-call, say so in the posting.

The template

Download .md

Data Engineer

[Company name] · [City, Province] · [Remote / Hybrid, X days in office / On-site] · [Full-time, permanent]

Pay

$[X] to $[Y] per year.

[If there is a bonus or commission tied to hours, output or results, add it here. Example: "Plus a bonus of up to [X]% of salary, based on [what it's based on]."]

About this posting

  • This posting is for an existing vacancy. [Or: "This posting is not for an existing vacancy." Pick one.]
  • We [use / do not use] artificial intelligence (AI) to screen, assess or select applicants. [If you use it, you must say so. You don't have to name the tool.]
  • If we interview you, we will tell you within 45 days of your last interview whether we have made a hiring decision.
  • We offer accommodation for disabilities at every step of hiring. Tell [name, email] what you need and we will work it out with you.

About us

[Two or three sentences. What the business does and why data matters to it. Give a sense of scale, for example "[X] million events a day."]

What you'll do

  • Build and run data pipelines that move data from source systems into clean tables people can query.
  • Build and tune data models in [your warehouse, for example Snowflake, BigQuery or Redshift].
  • Add data quality checks and alerts so we catch problems before the people using the data do.
  • Work with analytics and ML teams to give them data they can trust.
  • Own scheduling, dependencies and recovery when a job fails.
  • Keep data lineage and docs up to date.

What you need

  • About [3] years of running data pipelines in production, or the same skill from other work.
  • Strong SQL. You can write hard queries and speed up slow ones.
  • [Python or Scala] for data work.
  • Hands-on work with [your orchestration tool, for example Airflow, Dagster or dbt].
  • A good grasp of data modelling, for example star schemas.

Nice to have

  • Streaming data, for example [Kafka or Kinesis].
  • Infrastructure as code, for example [Terraform].
  • [One more tool you actually use].

What we offer

  • [Health, dental and vision coverage]
  • [Vacation: X weeks a year]
  • [Equity, if any, and how it vests]
  • [On-call: how often, and how it's paid or given back as time off]
  • [Learning budget: $X a year]

How to apply

Send your resume to [email or link]. A short note about a pipeline you're proud of helps.

We read every application.

Notes before you post. Delete this section before posting. General information, not legal advice.

  1. Ontario, 25 or more employees: the pay line, the AI line and the vacancy line are required. Sources: ESA ss. 8.2, 8.4, 8.5 (https://www.ontario.ca/laws/statute/00e41) and O. Reg. 476/24 (https://www.ontario.ca/laws/regulation/r24476).
  2. Keep the gap between $X and $Y at $50,000 or less. Source: O. Reg. 476/24, s. 4.
  3. Don't ask for Canadian experience in the ad or the application form. Source: ESA s. 8.3. The OHRC calls a strict Canadian experience rule discrimination on its face (https://www.ohrc.on.ca/en/policy-removing-canadian-experience-barrier).
  4. Tell each person you interview whether you've made a hiring decision within 45 days of their last interview. Source: ESA s. 8.6 and O. Reg. 476/24, s. 5.
  5. Keep every posted version, any linked pages and the application form for 3 years. Source: ESA s. 15(7.1) and the Ontario guide (https://www.ontario.ca/document/your-guide-employment-standards-act-0/requirements-related-publicly-advertised-job).
  6. Ontario employers must tell the public that accommodation is available for applicants with disabilities. Source: O. Reg. 191/11, s. 22 (https://www.ontario.ca/laws/regulation/110191).
  7. BC: post the expected pay or range. Don't ask about past pay, directly or through anyone else. Source: Pay Transparency Act, ss. 2 and 3 (https://www.bclaws.gov.bc.ca/civix/document/id/complete/statreg/23018).
  8. Don't word the ad in a way that points to age, sex, race, religion, family status, disability or any other protected ground. Sources: Ontario Human Rights Code s. 23(1) (https://www.ontario.ca/laws/statute/90h19), Manitoba Human Rights Code s. 14(3) (https://web2.gov.mb.ca/laws/statutes/ccsm/h175.php), Canadian Human Rights Act s. 8 (https://laws-lois.justice.gc.ca/eng/acts/h-6/FullText.html).

Sources