Data Engineer (Azure, Fabric, Databricks)
Chicago, IL
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingThe Data Engineer is responsible for designing, implementing, and supporting modern data platforms using Microsoft Fabric and Databricks, with a strong emphasis on lakehouse architecture, analytics engineering, and semantic modeling.
You will collaborate with client stakeholders, Collectiv consultants, and cross-functional teams to deliver data platforms that support reporting, advanced analytics, and self-service BI.
Design and implement modern data platforms leveraging Microsoft Fabric (OneLake, Lakehouse, Data Factory, Power BI) and Databricks (Spark, Delta Lake, SQL Warehouses)
Develop and maintain semantic models that enable performant reporting and self-service analytics
Write, optimize, and tune SQL and Spark-based transformations for large-scale analytical workloads
From the employer’s posting
The Data Engineer is responsible for designing, implementing, and supporting modern data platforms using Microsoft Fabric and Databricks, with a strong emphasis on lakehouse architecture, analytics engineering, and semantic modeling. This role is client-facing and requires translating business requirements into scalable technical solutions while adhering to data engineering best practices.
You will collaborate with client stakeholders, Collectiv consultants, and cross-functional teams to deliver data platforms that support reporting, advanced analytics, and self-service BI.
Client Delivery & Solution Design Design and implement modern data platforms leveraging Microsoft Fabric (OneLake, Lakehouse, Data Factory, Power BI) and Databricks (Spark, Delta Lake, SQL Warehouses) Build and optimize data ingestion, transformation, and orchestration pipelines using ELT/ETL best practices
Analytics & BI Enablement Develop and maintain semantic models that enable performant reporting and self-service analytics Partner with analytics and business teams to deliver trusted datasets and dashboards (Power BI or equivalent)
Engineering Best Practices Write, optimize, and tune SQL and Spark-based transformations for large-scale analytical workloads Apply version control, CI/CD concepts, and code review standards to data engineering workflows
What you’ll bring
All qualificationsCore experience
- Bachelor's degree from an accredited university
- 4+ years of experience in data engineering, analytics engineering, or data platform consulting
- Hands-on experience with Microsoft Fabric and/or Databricks in production environments
- Strong SQL skills, including performance tuning and optimization
- Experience designing data models for analytics (star schemas, semantic models, lakehouse patterns)
- Experience working in cloud data platforms
Preferred experience
- experience with both strongly preferred
- Experience migrating or modernizing data platforms (e.g., legacy DW to lakehouse)
- Azure preferred
- Familiarity with Power BI dataset modeling and performance optimization
Qualification wording
Bachelor's degree from an accredited university
4+ years of experience in data engineering, analytics engineering, or data platform consulting
Hands-on experience with Microsoft Fabric and/or Databricks in production environments (experience with both strongly preferred)
Strong SQL skills, including performance tuning and optimization
Experience designing data models for analytics (star schemas, semantic models, lakehouse patterns)
Experience working in cloud data platforms (Azure preferred)
Experience migrating or modernizing data platforms (e.g., legacy DW to lakehouse)
Familiarity with Power BI dataset modeling and performance optimization
Tools in this posting
- SQL
- Azure
- Databricks
- Delta
- Spark
- Power BI
Source — Tool mentions in context
Client Delivery & Solution Design - Design and implement modern data platforms leveraging Microsoft Fabric (OneLake, Lakehouse, Data Factory, Power BI) and Databricks (Spark, Delta Lake, SQL Warehouses) - Build and optimize data ingestion, transformation, and orchestration pipelines using ELT/ETL best practices
Engineering Best Practices - Write, optimize, and tune SQL and Spark-based transformations for large-scale analytical workloads - Apply version control, CI/CD concepts, and code review standards to data engineering workflows
- Hands-on experience with Microsoft Fabric and/or Databricks in production environments (experience with both strongly preferred) - Strong SQL skills, including performance tuning and optimization - Experience designing data models for analytics (star schemas, semantic models, lakehouse patterns)
- Experience designing data models for analytics (star schemas, semantic models, lakehouse patterns) - Experience working in cloud data platforms (Azure preferred) - Ability to work independently in a client-facing consulting role
- Strong written and verbal communication skills - Relevant Azure certifications (e.g., Azure Solutions Architect, Azure Data Engineer), Fabric (DP-600, DP-700) certifications, and Databricks certifications are highly desirable What Success Looks Like in This Role
Role Overview The Data Engineer is responsible for designing, implementing, and supporting modern data platforms using Microsoft Fabric and Databricks, with a strong emphasis on lakehouse architecture, analytics engineering, and semantic modeling. This role is client-facing and requires translating business requirements into scalable technical solutions while adhering to data engineering best practices. You will collaborate with client stakeholders, Collectiv consultants, and cross-functional teams to deliver data platforms that support reporting, advanced analytics, and self-service BI.
- 4+ years of experience in data engineering, analytics engineering, or data platform consulting - Hands-on experience with Microsoft Fabric and/or Databricks in production environments (experience with both strongly preferred) - Strong SQL skills, including performance tuning and optimization
- Develop and maintain semantic models that enable performant reporting and self-service analytics - Partner with analytics and business teams to deliver trusted datasets and dashboards (Power BI or equivalent) - Ensure data quality, reliability, and usability across the analytics platform
- Experience migrating or modernizing data platforms (e.g., legacy DW to lakehouse) - Familiarity with Power BI dataset modeling and performance optimization - Experience integrating data platforms with downstream applications or APIs
Join Collectiv for a rewarding career in a fully remote work environment with quarterly in person team experiences and a competitive compensation. We provide a clear growth trajectory with professional development opportunities and a top-shelf benefits package. Enjoy unlimited time off and 100% covered health insurance, encompassing medical, dental, and vision plans for you and your family. Our comprehensive offerings, from a competitive 401(k) with a 4% match to educational assistance, tech stipend, and discounts on various goods and services, demonstrate our commitment to your well-being and success. At Collectiv, your career thrives with a perfect blend of remote flexibility, growth potential, and unparalleled benefits prioritizing your financial, physical, and emotional well-being. Collectiv is the leading boutique consulting and strategy firm specializing in Analytics, Planning and AI with Power BI and the Microsoft Data Stack. Our mission at Collectiv is simple: We help enterprises make better decisions.
Job description
Role Overview
The Data Engineer is responsible for designing, implementing, and supporting modern data platforms using Microsoft Fabric and Databricks, with a strong emphasis on lakehouse architecture, analytics engineering, and semantic modeling. This role is client-facing and requires translating business requirements into scalable technical solutions while adhering to data engineering best practices.
You will collaborate with client stakeholders, Collectiv consultants, and cross-functional teams to deliver data platforms that support reporting, advanced analytics, and self-service BI.
Key Responsibilities
Client Delivery & Solution Design
- Design and implement modern data platforms leveraging Microsoft Fabric (OneLake, Lakehouse, Data Factory, Power BI) and Databricks (Spark, Delta Lake, SQL Warehouses)
- Build and optimize data ingestion, transformation, and orchestration pipelines using ELT/ETL best practices
- Develop scalable lakehouse architectures that support analytics, reporting, and downstream data products
- Translate business and analytical requirements into technical designs and data models
Analytics & BI Enablement
- Develop and maintain semantic models that enable performant reporting and self-service analytics
- Partner with analytics and business teams to deliver trusted datasets and dashboards (Power BI or equivalent)
- Ensure data quality, reliability, and usability across the analytics platform
Engineering Best Practices
- Write, optimize, and tune SQL and Spark-based transformations for large-scale analytical workloads
- Apply version control, CI/CD concepts, and code review standards to data engineering workflows
- Ensure solutions meet quality criteria related to performance, scalability, and maintainability
Consulting & Collaboration
- Work directly with client stakeholders to gather requirements, communicate technical concepts, and manage expectations
- Collaborate with project managers, architects, and fellow consultants to align technical delivery with project goals
- Contribute to internal documentation, reusable patterns, and knowledge sharing across Collectiv
Required Qualifications
- Bachelor's degree from an accredited university
- 4+ years of experience in data engineering, analytics engineering, or data platform consulting
- Hands-on experience with Microsoft Fabric and/or Databricks in production environments (experience with both strongly preferred)
- Strong SQL skills, including performance tuning and optimization
- Experience designing data models for analytics (star schemas, semantic models, lakehouse patterns)
- Experience working in cloud data platforms (Azure preferred)
- Ability to work independently in a client-facing consulting role
Preferred Qualifications
- Experience migrating or modernizing data platforms (e.g., legacy DW to lakehouse)
- Familiarity with Power BI dataset modeling and performance optimization
- Experience integrating data platforms with downstream applications or APIs
- Consulting experience with multiple clients or industries
- Strong written and verbal communication skills
- Relevant Azure certifications (e.g., Azure Solutions Architect, Azure Data Engineer), Fabric (DP-600, DP-700) certifications, and Databricks certifications are highly desirable
What Success Looks Like in This Role
- Clients trust you as a technical advisor for their data platform decisions
- Delivered solutions are scalable, well-documented, and aligned to best practices
- Business users are enabled through reliable data models and analytics-ready datasets
- You actively contribute to Collectiv’s data platform standards and consulting excellence
Join Collectiv for a rewarding career in a fully remote work environment with quarterly in person team experiences and a competitive compensation. We provide a clear growth trajectory with professional development opportunities and a top-shelf benefits package. Enjoy unlimited time off and 100% covered health insurance, encompassing medical, dental, and vision plans for you and your family. Our comprehensive offerings, from a competitive 401(k) with a 4% match to educational assistance, tech stipend, and discounts on various goods and services, demonstrate our commitment to your well-being and success. At Collectiv, your career thrives with a perfect blend of remote flexibility, growth potential, and unparalleled benefits prioritizing your financial, physical, and emotional well-being.
Collectiv is the leading boutique consulting and strategy firm specializing in Analytics, Planning and AI with Power BI and the Microsoft Data Stack.
Our mission at Collectiv is simple: We help enterprises make better decisions.
Our Core Values:
Growth Mindset – Bring solutions, not problems.
Excel with Humility – Be humbly brilliant.
Communicate Actively and Empathetically – Listen, ask, understand, help.
Work Hard, Play Hard – Results are proportional to effort.
Keep Calm and Carry On – Stay cool, calm and Collectiv.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on collectiv.breezy.hr. The employer’s form will show what is required.
Already applied? Track this application
Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Chicago, IL
- You actively contribute to Collectiv’s data platform standards and consulting excellence Join Collectiv for a rewarding career in a fully remote work environment with quarterly in person team experiences and a competitive compensation. We provide a clear growth trajectory with professional development opportunities and a top-shelf benefits package. Enjoy unlimited time off and 100% covered health insurance, encompassing medical, dental, and vision plans for you and your family. Our comprehensive offerings, from a competitive 401(k) with a 4% match to educational assistance, tech stipend, and discounts on various goods and services, demonstrate our commitment to your well-being and success. At Collectiv, your career thrives with a perfect blend of remote flexibility, growth potential, and unparalleled benefits prioritizing your financial, physical, and emotional well-being. Collectiv is the leading boutique consulting and strategy firm specializing in Analytics, Planning and AI with Power BI and the Microsoft Data Stack.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Jun 2, 2026
- Recorded sightings
- 48
- Last seen by us
- Oct 6, 2026
- Employer says posted
- Apr 1, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Report an errorSee how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.