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Product Engineering (Fabric Data Engineering)

Canadian Head Office (It)

Live, first seen by us 69 days ago
Pay
$80,900–120,000/year — pay source
Compensation Expected compensation for this role ranges from $ 80,900 - 120,000 annually. Actual salary offered to successful candidates will vary based on their skills and experience. Joining our team isn’t just a job — it’s an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. One where you can shape the future of protection while supporting causes that mean the most to you. Joining our team means being part of something bigger – a winning team making a meaningful impact.
Read the full posting
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Design and maintain the Fabric workspace, OneLake, and Lakehouse architecture, including Bronze ingestion feeds

  • Build Silver cleansing and reconciliation logic and Gold dimensional models with SCD2 history

  • Build and maintain Azure DevOps CI/CD pipelines across dev, test, and production

  • Build Power BI Direct Lake semantic models and reporting layers on the Gold layer

  • Own the Fabric and OneLake security model, including row- and column-level security

From the employer’s posting
Design /Code and own the Microsoft Fabric workspace, OneLake, Lakehouse, and Warehouse architecture, including Bronze-layer ingestion patterns
Design, build, and optimize Silver-layer cleansing, deduplication, conformance, and reconciliation logic
Build and maintain Azure DevOps CI/CD pipelines across development, test, and production environments
Design, build, and maintain Power BI Direct Lake semantic models, DAX measures
Own the Fabric and OneLake security model, including workspace roles, OneLake RBAC, row-level security, column-level security
Apply at Allstate

Posting record

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Status in our records
Live
First seen by us
Aug 26, 202669 days ago
Recorded sightings
205
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 69

Up longer than most. Similar jobs usually come down between day 5 and day 54.

From 10,736 similar postings that came down. Coming down is not always a hire.

Allstate is hiring

15 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Engineer hiring is picking up
  • Takes jobs down quickly
  • 7% of open jobs were reposted
Hiring record

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
  • Azure
  • Delta Lake
  • Power BI
  • Spark
  • PySpark
Where the posting names them
- Microsoft Fabric engineering, including Workspaces, OneLake, Lakehouse, Warehouse, Notebooks, Data Pipelines, Dataflows, and Direct Lake. - Data engineering and transformation development using SQL, PySpark, Python, Spark, Delta Lake, and modern ELT patterns. - Bronze, Silver, and Gold Lakehouse architecture, including ingestion, cleansing, conformance, reconciliation, and business-ready data mart design.
Skills Azure Devops, CI/CD, Data Engineering, Data Governance, Data Lakehouse Architecture, Data Quality, Data Security, Data Transformation, Python (Programming Language), Semantic Modeling Compensation
- Establish and enforce Fabric data build standards, governance practices, reusable engineering patterns, naming conventions, and code-review expectations across the delivery team. - Build and maintain Azure DevOps CI/CD pipelines across development, test, and production environments, including approval gates, service principal management, deployment parameterization, and repeatable release processes. - Design, build, and optimize Silver-layer cleansing, deduplication, conformance, and reconciliation logic to create trusted, audit-ready datasets for downstream analytics.
- Use Copilot in Power BI and engineering productivity tools such as GitHub Copilot to accelerate modeling, report creation, documentation, and validation while ensuring all generated outputs meet enterprise quality standards. - Establish operational monitoring and observability using Fabric Capacity Metrics, Monitoring Hub, workspace monitoring, Azure Monitor, and Log Analytics to proactively identify performance or reliability issues. - Troubleshoot production pipeline, data-quality, semantic model, and report-performance issues; lead root-cause analysis and coordinate remediation with platform, analytics, business, and support teams.
- Delta table performance optimization using OPTIMIZE, Z-Order, V-Order, Liquid Clustering, VACUUM, Change Data Feed, partitioning strategy, and Spark workload tuning. - Azure DevOps and CI/CD skills, including Git-based development, pull requests, approval gates, environment promotion, deployment automation, and release governance. - Power BI semantic model development, including Direct Lake models, relationships, DAX measures, calculation logic, dataset security, and report performance optimization.
- Data quality engineering, including automated validation, reconciliation checks, exception handling, lineage validation, auditability, and regulatory reporting support. - Monitoring and operational support using Fabric Capacity Metrics, Monitoring Hub, workspace monitoring, Azure Monitor, Log Analytics, incident triage, and root-cause analysis. - Insurance domain understanding, especially Auto and Property policy, claims, billing, actuarial, underwriting, regulatory reporting, loss ratio, and combined ratio concepts.
Job description: The Product Engineering (Fabric Data Engineering) role combines platform engineering, data engineering, dimensional modeling, Gold-layer delivery, and AI-augmented analytics enablement within Microsoft Fabric. This role is accountable for designing and operating the team’s Fabric workspace, OneLake/Lakehouse architecture, CI/CD release process, Bronze ingestion patterns, Silver/Gold transformation pipelines, Delta table performance strategy, security model, and observability framework. The role also owns the end-to-end data product lifecycle from raw ingestion through trusted dimensional models and Power BI semantic models, ensuring Auto and Property insurance data is accurate, reusable, performant, governed, and ready for business self-service, regulatory reporting, Copilot-assisted analytics, and downstream application/API consumption. Accountabilities:
- Implement automated data-quality controls, including row-count validation, measure reconciliation, SCD2 integrity checks, lineage validation, and exception reporting. - Optimize Delta tables and Fabric workloads using techniques such as OPTIMIZE, Z-Order, V-Order, Liquid Clustering, VACUUM, Change Data Feed, and Spark resource tuning based on actual workload and Power BI query patterns. - Own the Fabric and OneLake security model, including workspace roles, OneLake RBAC, row-level security, column-level security, object-level security, Microsoft Purview sensitivity labels, and DLP alignment.
- Dimensional modeling expertise, including Kimball methodology, star schemas, fact/dimension design, grain definition, Slowly Changing Dimensions Type 2, and incremental load patterns. - Delta table performance optimization using OPTIMIZE, Z-Order, V-Order, Liquid Clustering, VACUUM, Change Data Feed, partitioning strategy, and Spark workload tuning. - Azure DevOps and CI/CD skills, including Git-based development, pull requests, approval gates, environment promotion, deployment automation, and release governance.
- Own the Fabric and OneLake security model, including workspace roles, OneLake RBAC, row-level security, column-level security, object-level security, Microsoft Purview sensitivity labels, and DLP alignment. - Design, build, and maintain Power BI Direct Lake semantic models, DAX measures, dataset access controls, and performance-tuned reporting layers directly on top of the Gold layer. - Configure semantic models for AI and Copilot readiness, including AI data schemas, verified answers, clear table/column/measure descriptions, and business-friendly metadata.
- Configure semantic models for AI and Copilot readiness, including AI data schemas, verified answers, clear table/column/measure descriptions, and business-friendly metadata. - Use Copilot in Power BI and engineering productivity tools such as GitHub Copilot to accelerate modeling, report creation, documentation, and validation while ensuring all generated outputs meet enterprise quality standards. - Establish operational monitoring and observability using Fabric Capacity Metrics, Monitoring Hub, workspace monitoring, Azure Monitor, and Log Analytics to proactively identify performance or reliability issues.
- Partner with business stakeholders across underwriting, claims, actuarial, finance, and regulatory reporting teams to translate data requirements into scalable Fabric data products and explain analytical outputs in business terms. - Mentor engineers, review pull requests, support capacity planning, and promote shared engineering practices across data engineering, analytics engineering, and Power BI development activities. Qualifications:
- Azure DevOps and CI/CD skills, including Git-based development, pull requests, approval gates, environment promotion, deployment automation, and release governance. - Power BI semantic model development, including Direct Lake models, relationships, DAX measures, calculation logic, dataset security, and report performance optimization. - AI and Copilot readiness for analytics, including semantic model descriptions, verified answers, AI data schemas, business-friendly metadata, and validation of AI-generated outputs.

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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 ↗

At Allstate, great things happen when our people work together to protect families and their belongings from life’s uncertainties. And for more than 90 years, our innovative drive has kept us a step ahead of our customers’ evolving needs. From advocating for seat belts, air bags and graduated driving laws, to being an industry leader in pricing sophistication, telematics, and, more recently, device and identity protection. 

Job Description

Who is Allstate:
Allstate Insurance Company of Canada is a leading home and auto insurer focused on providing its customers prevention and protection products and services for every stage of life. Serving Canadians since 1953, Allstate strives to reassure both customers and employees with its “You’re in Good Hands®” promise and is proud to have been named a Best Employer in Canada for nine consecutive years. Allstate is committed to making a positive difference in the communities in which it operates through partnerships with charitable organizations, employee giving and volunteerism. To learn more, visit www.allstate.ca. For safety tips and advice, visit www.goodhandsadvice.ca.

Through our Employee Value Proposition, we have worked hard to develop and nurture a culture where employees feel valued, experience personal growth, have career options and truly enjoy the work they do. 

Role Designation: Hybrid
 

Benefits to joining Allstate

  • Flexible Work Arrangements. 
  • Employee discounts (15% on auto and property insurance, plus many other products and services). 
  • Good Office program (receive up to $400 back after purchasing office equipment). 
  • Student Loan Payment Matching Program for Government Student loans. 
  • Comprehensive Retirement Savings Program with employer matched contributions. 
  • Annual Wellness allowance to support employees with improving health and wellbeing. 
  • Personal days. 
  • Tuition Reimbursement. 
  • Working within the community and giving back. 

Job description:

The Product Engineering (Fabric Data Engineering) role combines platform engineering, data engineering, dimensional modeling, Gold-layer delivery, and AI-augmented analytics enablement within Microsoft Fabric. This role is accountable for designing and operating the team’s Fabric workspace, OneLake/Lakehouse architecture, CI/CD release process, Bronze ingestion patterns, Silver/Gold transformation pipelines, Delta table performance strategy, security model, and observability framework. The role also owns the end-to-end data product lifecycle from raw ingestion through trusted dimensional models and Power BI semantic models, ensuring Auto and Property insurance data is accurate, reusable, performant, governed, and ready for business self-service, regulatory reporting, Copilot-assisted analytics, and downstream application/API consumption.

Accountabilities:

  • Design /Code and own the Microsoft Fabric workspace, OneLake, Lakehouse, and Warehouse architecture, including Bronze-layer ingestion patterns for policy, claims, billing, and third-party vendor data feeds.
  • Establish and enforce Fabric data build standards, governance practices, reusable engineering patterns, naming conventions, and code-review expectations across the delivery team.
  • Build and maintain Azure DevOps CI/CD pipelines across development, test, and production environments, including approval gates, service principal management, deployment parameterization, and repeatable release processes.
  • Design, build, and optimize Silver-layer cleansing, deduplication, conformance, and reconciliation logic to create trusted, audit-ready datasets for downstream analytics.
  • Design and maintain Gold-layer dimensional models, star schemas, Slowly Changing Dimension Type 2 history tracking, incremental load patterns, and business-ready marts using Kimball and analytics-engineering principles.
  • Implement automated data-quality controls, including row-count validation, measure reconciliation, SCD2 integrity checks, lineage validation, and exception reporting.
  • Optimize Delta tables and Fabric workloads using techniques such as OPTIMIZE, Z-Order, V-Order, Liquid Clustering, VACUUM, Change Data Feed, and Spark resource tuning based on actual workload and Power BI query patterns.
  • Own the Fabric and OneLake security model, including workspace roles, OneLake RBAC, row-level security, column-level security, object-level security, Microsoft Purview sensitivity labels, and DLP alignment.
  • Design, build, and maintain Power BI Direct Lake semantic models, DAX measures, dataset access controls, and performance-tuned reporting layers directly on top of the Gold layer.
  • Configure semantic models for AI and Copilot readiness, including AI data schemas, verified answers, clear table/column/measure descriptions, and business-friendly metadata.
  • Use Copilot in Power BI and engineering productivity tools such as GitHub Copilot to accelerate modeling, report creation, documentation, and validation while ensuring all generated outputs meet enterprise quality standards.
  • Establish operational monitoring and observability using Fabric Capacity Metrics, Monitoring Hub, workspace monitoring, Azure Monitor, and Log Analytics to proactively identify performance or reliability issues.
  • Troubleshoot production pipeline, data-quality, semantic model, and report-performance issues; lead root-cause analysis and coordinate remediation with platform, analytics, business, and support teams.
  • Expose Lakehouse, Warehouse, Gold-layer, or semantic-model data through Fabric API for GraphQL or REST where programmatic or application-level consumption is required.
  • Maintain architecture documentation, runbooks, lineage definitions, business glossaries, onboarding materials, and self-service guidance for technical and non-technical stakeholders.
  • Partner with business stakeholders across underwriting, claims, actuarial, finance, and regulatory reporting teams to translate data requirements into scalable Fabric data products and explain analytical outputs in business terms.
  • Mentor engineers, review pull requests, support capacity planning, and promote shared engineering practices across data engineering, analytics engineering, and Power BI development activities.

Qualifications:

  • Microsoft Fabric engineering, including Workspaces, OneLake, Lakehouse, Warehouse, Notebooks, Data Pipelines, Dataflows, and Direct Lake.
  • Data engineering and transformation development using SQL, PySpark, Python, Spark, Delta Lake, and modern ELT patterns.
  • Bronze, Silver, and Gold Lakehouse architecture, including ingestion, cleansing, conformance, reconciliation, and business-ready data mart design.
  • Dimensional modeling expertise, including Kimball methodology, star schemas, fact/dimension design, grain definition, Slowly Changing Dimensions Type 2, and incremental load patterns.
  • Delta table performance optimization using OPTIMIZE, Z-Order, V-Order, Liquid Clustering, VACUUM, Change Data Feed, partitioning strategy, and Spark workload tuning.
  • Azure DevOps and CI/CD skills, including Git-based development, pull requests, approval gates, environment promotion, deployment automation, and release governance.
  • Power BI semantic model development, including Direct Lake models, relationships, DAX measures, calculation logic, dataset security, and report performance optimization.
  • AI and Copilot readiness for analytics, including semantic model descriptions, verified answers, AI data schemas, business-friendly metadata, and validation of AI-generated outputs.
  • Data governance and security, including OneLake RBAC, workspace roles, row-level security, column-level security, object-level security, Microsoft Purview sensitivity labels, lineage, and DLP alignment.
  • Data quality engineering, including automated validation, reconciliation checks, exception handling, lineage validation, auditability, and regulatory reporting support.
  • Monitoring and operational support using Fabric Capacity Metrics, Monitoring Hub, workspace monitoring, Azure Monitor, Log Analytics, incident triage, and root-cause analysis.
  • Insurance domain understanding, especially Auto and Property policy, claims, billing, actuarial, underwriting, regulatory reporting, loss ratio, and combined ratio concepts.
  • API and integration awareness, including Fabric API for GraphQL, REST-based consumption patterns, and governed downstream application access.
  • Documentation and communication skills, including architecture documentation, runbooks, business glossaries, data lineage, onboarding materials, and stakeholder-ready explanations.
  • Technical leadership skills, including mentoring engineers, reviewing code, defining reusable patterns, enforcing standards, supporting capacity planning, and collaborating across platform, analytics, and business teams.

Allstate Canada Group has policies and practices that provide workplace accommodations. If you require accommodation, please let us know and we will work with you to meet your needs. 

#LI-GL1

Skills

Azure Devops, CI/CD, Data Engineering, Data Governance, Data Lakehouse Architecture, Data Quality, Data Security, Data Transformation, Python (Programming Language), Semantic Modeling

 

Compensation

Expected compensation for this role ranges from $ 80,900 - 120,000 annually.  Actual salary offered to successful candidates will vary based on their skills and experience.

Joining our team isn’t just a job — it’s an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. One where you can shape the future of protection while supporting causes that mean the most to you. Joining our team means being part of something bigger – a winning team making a meaningful impact.

Allstate Canada Group uses AI technology tools to assist in screening, selecting, assessing, and scheduling interviews with candidates as part of the recruitment process.

This job posting is for a current open role within the organization.

Source details

View original posting ↗

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Pay
Compensation Expected compensation for this role ranges from $ 80,900 - 120,000 annually. Actual salary offered to successful candidates will vary based on their skills and experience. Joining our team isn’t just a job — it’s an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. One where you can shape the future of protection while supporting causes that mean the most to you. Joining our team means being part of something bigger – a winning team making a meaningful impact.
Location & working pattern

Canadian Head Office (It)

Through our Employee Value Proposition, we have worked hard to develop and nurture a culture where employees feel valued, experience personal growth, have career options and truly enjoy the work they do. Role Designation: Hybrid Benefits to joining Allstate
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