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Data Engineer

Pay
CAD 90,000–100,000/year — pay source
Compensation and Benefits This position has a starting salary range of $90,000 - $100,000 CAD per year. The range represents what we reasonably and in good faith expect to pay for the role at the time of posting. An employee’s pay within the range is determined by a number of factors, including relevant skills, education, qualifications, experience, performance, business or organizational needs, and geographic location. Eligible employees may participate in medical, dental, vision, disability, life insurance, retirement savings programs, paid time off, wellness programs, and other company-sponsored benefits. Benefits vary by country and employment status.
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Work setting
Remote — work setting source
Job Title: Data Engineer Location: Remote | Canada Reports to: Sr. Manager - Data Engineering & Data Science
Listed location: Remote Canada
Read the full posting
Employment
Full-time — employment source
Reports to: Sr. Manager - Data Engineering & Data Science Employment Type: Full-time This is an existing vacancy About the Role:
Employment type in the employer’s posting: Full time
From the employer’s posting

Before you apply

Work authorization
Must already have the right to workCandidates must be legally authorized to work in the country where employment is offered

What you’ll work on

Full posting
  • Build Snowflake semantic views and a versioned metric registry with approved metric definitions

  • Design, run, and maintain repeatable ETL/ELT data pipelines and own their reliability

  • Build and maintain business context such as glossaries, metric definitions, and rules, approved by business owners

  • Help build canonical master data sets, such as master vehicle, dealer, and incentives data

  • Lead end-to-end data engineering projects and mentor junior data engineers

From the employer’s posting
Design, build, validate, and publish governed Snowflake semantic views and a versioned metric registry
Design, troubleshoot, and execute repeatable data pipelines on Snowflake
Build and maintain the business context that makes data AI-ready: business terms, glossaries, metric definitions, rules, and hierarchies
Help build canonical “master” data sets where multiple sources of truth exist today
Lead end-to-end data engineering projects, and mentor and guide junior data engineers

What you’ll bring

All qualifications

Core experience

  • Hands-on experience with Snowflake is strongly preferred (e.g., Snowpark, Dynamic Tables, role-based access control), and semantic views or Cortex experience is a big plus.
  • Ability and willingness to learn in a fast-paced environment, with a resilient work ethic
  • Experience with other cloud platforms such as Google Cloud (BigQuery), AWS, or Palantir is also valued
  • Experience building semantic layers or governed metrics (e.g., Snowflake semantic views, dbt Semantic Layer, LookML, AtScale, Cube), with a strong base in dimensional modeling (facts, dimensions, grain)
  • Familiarity with ontologies, knowledge graphs, data catalogs, metadata management, and data governance (e.g., access control, PII handling, lineage)
  • Experience resolving data issues in creative and effective ways.

Preferred experience

  • Hands-on experience building an LLM application is a plus
Qualification wording
Hands-on experience with Snowflake is strongly preferred (e.g., Snowpark, Dynamic Tables, role-based access control), and semantic views or Cortex experience is a big plus. Experience with other cloud platforms such as Google Cloud (BigQuery), AWS, or Palantir is also valued
Ability and willingness to learn in a fast-paced environment, with a resilient work ethic
Experience building semantic layers or governed metrics (e.g., Snowflake semantic views, dbt Semantic Layer, LookML, AtScale, Cube), with a strong base in dimensional modeling (facts, dimensions, grain)
Familiarity with ontologies, knowledge graphs, data catalogs, metadata management, and data governance (e.g., access control, PII handling, lineage)
Experience resolving data issues in creative and effective ways. Business acumen and gut instincts to know when to say, “This doesn’t seem reasonable.”
Working knowledge of how AI applications use data: retrieval-augmented generation (RAG), embeddings and vector search, context and prompt design, tool calling, AI agents, and MCP. Hands-on experience building an LLM application is a plus
Education & alternatives
- Independent professional who can take a vision and implement with limited instruction - Bachelor’s degree (required), with a background in statistics, machine learning, computer science, finance, engineering, or mathematics preferred - An effective cross functional communicator in both written and verbal skills
- Ability and willingness to learn in a fast-paced environment, with a resilient work ethic - At least 5 yrs of professional experience with a Bachelor’s degree or 3 yrs with a Graduate degree as a full-time professional (non-academic) experience in data engineering and quantitative analytics, contributing to business impact through data-driven solutions Compensation and Benefits

Benefits in the posting

Full benefits wording
  • This position has a starting salary range of $90,000 - $100,000 CAD per year. The range represents what we reasonably and in good faith expect to pay for the role at the time of posting. An employee’s pay within the range is determined by a number of factors, including relevant skills, education, qualifications, experience, performance, business or organizational needs, and geographic location.
  • Eligible employees may participate in medical, dental, vision, disability, life insurance, retirement savings programs, paid time off, wellness programs, and other company-sponsored benefits. Benefits vary by country and employment status.
  • Why Join JD Power

From the employer’s posting.

Apply at Jdpa

Posting record

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Status in our records
Live
First seen by us
Oct 10, 202624 days ago
Recorded sightings
24
Last seen by us
Nov 4, 2026

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See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • BigQuery
  • dbt
  • Snowflake
  • GCP
Where the posting names them
Required Qualifications: - Must have: strong, hands-on proficiency in both Python and SQL. You use both every day to build, test, and debug production data pipelines - Must have: proven production experience in designing, building, and running ETL/ELT pipelines that bring together data from multiple sources, with ownership of their robustness and output data quality (e.g., idempotent jobs, monitoring and alerting, automated data quality checks)
- Software engineering background or experience is a plus: Git and code review, automated testing, CI/CD, and modular, reusable code - Hands-on experience with Snowflake is strongly preferred (e.g., Snowpark, Dynamic Tables, role-based access control), and semantic views or Cortex experience is a big plus. Experience with other cloud platforms such as Google Cloud (BigQuery), AWS, or Palantir is also valued - Experience building semantic layers or governed metrics (e.g., Snowflake semantic views, dbt Semantic Layer, LookML, AtScale, Cube), with a strong base in dimensional modeling (facts, dimensions, grain)
- Partner with AI engineers to connect semantic views, metrics, and search services to Cortex Analyst and Cortex Agents - Design, troubleshoot, and execute repeatable data pipelines on Snowflake (and on our current Google Cloud/BigQuery platform during the transition), in which you’re finding bottlenecks and ways to become incrementally more efficient. You own the reliability of these pipelines and the quality of the data they produce - Collaborate with stakeholders to gather and understand data processing requirements, with consistent proactive demonstration of business acumen and market dynamics
- Hands-on experience with Snowflake is strongly preferred (e.g., Snowpark, Dynamic Tables, role-based access control), and semantic views or Cortex experience is a big plus. Experience with other cloud platforms such as Google Cloud (BigQuery), AWS, or Palantir is also valued - Experience building semantic layers or governed metrics (e.g., Snowflake semantic views, dbt Semantic Layer, LookML, AtScale, Cube), with a strong base in dimensional modeling (facts, dimensions, grain) - Working knowledge of how AI applications use data: retrieval-augmented generation (RAG), embeddings and vector search, context and prompt design, tool calling, AI agents, and MCP. Hands-on experience building an LLM application is a plus
This is an existing vacancy About the Role: JD Power is looking for a data engineer with excellent quantitative and analytical skills to help make our data AI-ready. Our ideal candidates are determined to use their skills to combine multiple data sources together, and to add clear business meaning on top of them, so that both people and AI applications can answer complex client questions around vehicle transactions, incentives, valuations, market readiness, and customer purchase decisions. You’ll work hands on with data on Snowflake to build semantic views, governed metrics, and context layers that power AI assistants and agents, and to improve and maintain existing capabilities. We make data products that solve problems for the auto industry. Every data engineer will work on projects that go into production and directly impact new and existing products. In this role, your work decides whether our AI products give accurate, traceable answers instead of guesses.
We make data products that solve problems for the auto industry. Every data engineer will work on projects that go into production and directly impact new and existing products. In this role, your work decides whether our AI products give accurate, traceable answers instead of guesses. Grow as a data engineer as part of a medium sized team, where data engineering and AI engineering meet. You will build data pipelines, semantic views, and context layers on Snowflake, deploy them in the cloud, and build monitoring & QA suites, including tests for AI answer quality. The team is an experienced set of creative thinkers who are uncovering new and emerging consumer dynamics in an industry starting to go through rapid disruption. We are moving our key data to Snowflake and making it AI-ready, so our AI assistants and agents can give clients accurate, trusted answers.
Grow as a data engineer as part of a medium sized team, where data engineering and AI engineering meet. You will build data pipelines, semantic views, and context layers on Snowflake, deploy them in the cloud, and build monitoring & QA suites, including tests for AI answer quality. The team is an experienced set of creative thinkers who are uncovering new and emerging consumer dynamics in an industry starting to go through rapid disruption. We are moving our key data to Snowflake and making it AI-ready, so our AI assistants and agents can give clients accurate, trusted answers. We want data engineer candidates who can monitor, improve, and create data processes independently and with an eye toward continuous improvement. We need the capability to leverage the right data sets efficiently from an impressive set of data assets that is unrivaled in this space. We also want someone who is curious about AI, and who knows that AI is only as good as the data and business context behind it.
- Build and maintain the business context that makes data AI-ready: business terms, glossaries, metric definitions, rules, and hierarchies for a data domain (e.g., incentives, pricing, sales, dealers), reviewed and approved by business owners - Design, build, validate, and publish governed Snowflake semantic views and a versioned metric registry, so every application and AI agent uses one approved definition of each metric - Help build canonical “master” data sets where multiple sources of truth exist today (e.g., master vehicle/VIN, master dealer, master incentives)
- Help build canonical “master” data sets where multiple sources of truth exist today (e.g., master vehicle/VIN, master dealer, master incentives) - Prepare unstructured content (PDF documents, glossaries, FAQs, data dictionaries) for retrieval with Snowflake Cortex Search, with metadata and source traceability - Partner with AI engineers to connect semantic views, metrics, and search services to Cortex Analyst and Cortex Agents

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Job Description:

Job Title: Data Engineer

Location: Remote | Canada

Reports to: Sr. Manager - Data Engineering & Data Science

Employment Type: Full-time

This is an existing vacancy
 
About the Role:


JD Power is looking for a data engineer with excellent quantitative and analytical skills to help make our data AI-ready. Our ideal candidates are determined to use their skills to combine multiple data sources together, and to add clear business meaning on top of them, so that both people and AI applications can answer complex client questions around vehicle transactions, incentives, valuations, market readiness, and customer purchase decisions. You’ll work hands on with data on Snowflake to build semantic views, governed metrics, and context layers that power AI assistants and agents, and to improve and maintain existing capabilities.

 

We make data products that solve problems for the auto industry. Every data engineer will work on projects that go into production and directly impact new and existing products. In this role, your work decides whether our AI products give accurate, traceable answers instead of guesses.

Grow as a data engineer as part of a medium sized team, where data engineering and AI engineering meet. You will build data pipelines, semantic views, and context layers on Snowflake, deploy them in the cloud, and build monitoring & QA suites, including tests for AI answer quality.

The team is an experienced set of creative thinkers who are uncovering new and emerging consumer dynamics in an industry starting to go through rapid disruption. We are moving our key data to Snowflake and making it AI-ready, so our AI assistants and agents can give clients accurate, trusted answers.

We want data engineer candidates who can monitor, improve, and create data processes independently and with an eye toward continuous improvement. We need the capability to leverage the right data sets efficiently from an impressive set of data assets that is unrivaled in this space. We also want someone who is curious about AI, and who knows that AI is only as good as the data and business context behind it.

 

In this role, you will:

  • Daily immersion in automotive industry data
  • Build and maintain the business context that makes data AI-ready: business terms, glossaries, metric definitions, rules, and hierarchies for a data domain (e.g., incentives, pricing, sales, dealers), reviewed and approved by business owners
  • Design, build, validate, and publish governed Snowflake semantic views and a versioned metric registry, so every application and AI agent uses one approved definition of each metric
  • Help build canonical “master” data sets where multiple sources of truth exist today (e.g., master vehicle/VIN, master dealer, master incentives)
  • Prepare unstructured content (PDF documents, glossaries, FAQs, data dictionaries) for retrieval with Snowflake Cortex Search, with metadata and source traceability
  • Partner with AI engineers to connect semantic views, metrics, and search services to Cortex Analyst and Cortex Agents
  • Design, troubleshoot, and execute repeatable data pipelines on Snowflake (and on our current Google Cloud/BigQuery platform during the transition), in which you’re finding bottlenecks and ways to become incrementally more efficient. You own the reliability of these pipelines and the quality of the data they produce
  • Collaborate with stakeholders to gather and understand data processing requirements, with consistent proactive demonstration of business acumen and market dynamics
  • Contribute meaningfully to new product development, on top of production, by executing independently to plans (and by influencing the plans themselves) for new features on existing products, and for net-new products or approaches
  • Lead end-to-end data engineering projects, and mentor and guide junior data engineers
  • Interdisciplinary work: you’ll interact with multiple teams across the firm to implement solutions and improve processes. This includes Customer Success, Product Management, Product Development, Technology/Architecture, Data Engineering, Data Science, AI Engineering, Data Visualization, etc.

Required Qualifications:

  • Must have: strong, hands-on proficiency in both Python and SQL. You use both every day to build, test, and debug production data pipelines
  • Must have: proven production experience in designing, building, and running ETL/ELT pipelines that bring together data from multiple sources, with ownership of their robustness and output data quality (e.g., idempotent jobs, monitoring and alerting, automated data quality checks)
  • Software engineering background or experience is a plus: Git and code review, automated testing, CI/CD, and modular, reusable code
  • Hands-on experience with Snowflake is strongly preferred (e.g., Snowpark, Dynamic Tables, role-based access control), and semantic views or Cortex experience is a big plus. Experience with other cloud platforms such as Google Cloud (BigQuery), AWS, or Palantir is also valued
  • Experience building semantic layers or governed metrics (e.g., Snowflake semantic views, dbt Semantic Layer, LookML, AtScale, Cube), with a strong base in dimensional modeling (facts, dimensions, grain)
  • Working knowledge of how AI applications use data: retrieval-augmented generation (RAG), embeddings and vector search, context and prompt design, tool calling, AI agents, and MCP. Hands-on experience building an LLM application is a plus
  • Familiarity with ontologies, knowledge graphs, data catalogs, metadata management, and data governance (e.g., access control, PII handling, lineage)
  • Familiar with AI coding assistants (e.g., Claude Code, Cursor, GitHub Copilot), with hands-on experience using them in daily development work. You know their limits, and you review and test the code they produce before it goes to production
  • Experience resolving data issues in creative and effective ways. Business acumen and gut instincts to know when to say, “This doesn’t seem reasonable.”
  • Independent professional who can take a vision and implement with limited instruction
  • Bachelor’s degree (required), with a background in statistics, machine learning, computer science, finance, engineering, or mathematics preferred
  • An effective cross functional communicator in both written and verbal skills
  • Ability and willingness to learn in a fast-paced environment, with a resilient work ethic
  • At least 5 yrs of professional experience with a Bachelor’s degree or 3 yrs with a Graduate degree as a full-time professional (non-academic) experience in data engineering and quantitative analytics, contributing to business impact through data-driven solutions

 

Compensation and Benefits

This position has a starting salary range of $90,000 - $100,000 CAD per year. The range represents what we reasonably and in good faith expect to pay for the role at the time of posting. An employee’s pay within the range is determined by a number of factors, including relevant skills, education, qualifications, experience, performance, business or organizational needs, and geographic location.

 

Eligible employees may participate in medical, dental, vision, disability, life insurance, retirement savings programs, paid time off, wellness programs, and other company-sponsored benefits. Benefits vary by country and employment status.



Why Join JD Power

JD Power powers auto-related decisions through proprietary data, advanced analytics, deep industry expertise, and workflows that connect insight to action. Operating across North America, Europe, and Australia, we help customers make better decisions and achieve better outcomes.

 

As a virtual-first company, we offer flexible work arrangements, opportunities for learning and development, and a culture centered on the Values that guide how we work every day.

·       We power our customers’ success. Everything we do is focused on helping customers make better decisions and achieve better outcomes.

·       We are innovative, collaborative, and grounded in data. We combine advanced analytics with human expertise to deliver insight that holds up in the real world.

·       We make things easy. We turn complexity into clarity so teams can act faster and with confidence.

·       We get it done. We focus on execution, accountability, and results.

·       We start with trust and prove it every day. Independence, integrity, and credibility are the foundation of our work.


Equal Opportunity & Accommodations

JD Power is committed to employing a diverse workforce. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, or disability.

 

JD Power is committed to providing reasonable accommodations throughout the recruitment process for individuals with disabilities or other protected needs under applicable local laws. Please contact careers@jdpower.com for accommodation request.


Data Privacy

JD Power does not disclose your personal data to unauthorized third parties. However, as a global corporation consisting of multiple affiliated companies in various countries, JD Power has international sites and JD Power uses resources located throughout the world. JD Power may from time to time also use third parties to act on JD Power’s behalf. You agree to the fact that to the extent necessary your personal data may be transferred and/or disclosed to any company within JD Power group of companies as well as to third parties acting on JD Power’s behalf, including also transfers to servers and databases outside the country where you provided JD Power with your personal data. Such transfers may include for example transfers and/or disclosures outside the European Economic Area and in the United States of America. If you are a California or United Kingdom resident, additional disclosures about the information we collect and how we use that information can be found by clicking here.  

 

Applications

Candidates must be legally authorized to work in the country where employment is offered. JD Power does not provide employment sponsorship for this position.

 

This position is posted exclusively on https://www.jdpower.com/business/careers and select trusted job boards such as LinkedIn or Indeed. All official communication comes from email addresses ending in @jdpower.com or @jdpa.com. We will never ask for payment, equipment purchases, or upfront fees. We may take additional steps to verify candidate information to protect the integrity of our recruitment process.

 

To all recruitment agencies: JD Power does not accept unsolicited agency resumes and we are not responsible for any fees related to unsolicited resumes.

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Pay
Compensation and Benefits This position has a starting salary range of $90,000 - $100,000 CAD per year. The range represents what we reasonably and in good faith expect to pay for the role at the time of posting. An employee’s pay within the range is determined by a number of factors, including relevant skills, education, qualifications, experience, performance, business or organizational needs, and geographic location. Eligible employees may participate in medical, dental, vision, disability, life insurance, retirement savings programs, paid time off, wellness programs, and other company-sponsored benefits. Benefits vary by country and employment status.
Location & working pattern

Remote Canada

Job Title: Data Engineer Location: Remote | Canada Reports to: Sr. Manager - Data Engineering & Data Science
Work authorization
Applications Candidates must be legally authorized to work in the country where employment is offered. JD Power does not provide employment sponsorship for this position. This position is posted exclusively on https://www.jdpower.com/business/careers and select trusted job boards such as LinkedIn or Indeed. All official communication comes from email addresses ending in @jdpower.com or @jdpa.com. We will never ask for payment, equipment purchases, or upfront fees. We may take additional steps to verify candidate information to protect the integrity of our recruitment process.

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