Remote Data & Analytics Engineer — Lakehouse & Power BI

Collectiv; Chicago (IL); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote‑friendly

Competitive compensation

Unlimited time off

Health insurance

401(k) match

Education assistance

Job summary

Collectiv is seeking a Data & Analytics Engineer to blend data engineering with Power BI delivery, bridging backend data platforms and client‑facing analytics. You design lakehouse architectures on Fabric and Databricks, build scalable ELT/ETL pipelines, and deliver enterprise dashboards.

You translate ambiguous business needs into robust data models, optimize SQL and Spark workloads, and serve as a trusted advisor to enterprise clients while collaborating with cross‑functional teams.

Qualifications

• Bachelor’s degree required.
• 5+ years combined data engineering/analytics/BI consulting experience preferred.
• Hands-on production experience with Microsoft Fabric and/or Databricks strongly preferred.
• Advanced Power BI skills including complex modeling, DAX, and performance tuning.
• Experience designing analytics data models (star schemas, semantic models, lakehouse patterns).

Responsibilities

• Design and implement modern data platforms leveraging Microsoft Fabric and Databricks.
• Build and optimize ELT/ETL pipelines and lakehouse architectures.
• Develop enterprise-grade Power BI reports with semantic models and dashboards.
• Translate business requirements into scalable data models and technical solutions.
• Write and optimize SQL and Spark transformations for large-scale workloads.
• Apply CI/CD concepts and code-review standards to data workflows.

Skills

Power BI

SQL

Spark

Education

Bachelor’s degree from an accredited university

Tools

Microsoft Fabric

Databricks

Job description

Collectiv is seeking a Data & Analytics Engineer to blend data engineering with Power BI delivery, bridging backend data platforms and client‑facing analytics. You design lakehouse architectures on Fabric and Databricks, build scalable ELT/ETL pipelines, and deliver enterprise dashboards.

You translate ambiguous business needs into robust data models, optimize SQL and Spark workloads, and serve as a trusted advisor to enterprise clients while collaborating with cross‑functional teams.