Remote Data Engineer: Power BI & Analytics Pipelines

Particle41; United States; Remote; USD 100,000 - 140,000; Full time

Job summary

Particle41 is seeking a data engineer to design end-to-end data and reporting solutions with Power BI at the center. You will build scalable pipelines, analytics-ready storage, and semantic models to empower leadership decisions.

You will develop ETL/ELT pipelines, optimize data lakes or lakehouses, implement data quality checks, and create performant Power BI dashboards and models. Collaboration with product, engineering, and business teams is essential.

Qualifications

• Experience building data pipelines and analytics storage solutions.
• Strong Power BI skills, including semantic modeling, DAX, and Power Query.
• Ability to improve dashboard performance through model design, relationships, and aggregations.
• Understanding of data quality practices and reliable dataset refreshes.
• Ability to gather reporting needs from stakeholders and turn them into technical deliverables.
• Clear documentation and collaboration across product, engineering, and business teams.

Responsibilities

• Develop and maintain ETL/ELT pipelines from multiple sources.
• Build and optimize data lakes, warehouses, or lakehouses for analytics and reporting.
• Integrate data with validation, cleansing, transformation, and reconciliation checks.
• Create and tune Power BI dashboards, reports, and semantic models using dimensional schemas.
• Write and optimize DAX measures, calculated columns, KPIs, and Power Query transformations.
• Manage Power BI Service deployments, including refresh schedules, workspace access, and report sharing.

Skills

Power BI expertise

Data modeling

ETL/ELT design

Tools

Power BI Service

DAX

Power Query (M)

Job description

Particle41 is seeking a data engineer to design end-to-end data and reporting solutions with Power BI at the center. You will build scalable pipelines, analytics-ready storage, and semantic models to empower leadership decisions.

You will develop ETL/ELT pipelines, optimize data lakes or lakehouses, implement data quality checks, and create performant Power BI dashboards and models. Collaboration with product, engineering, and business teams is essential.