Data Engineer with power bi and Shopify data

Amaze Systems; Edina (MN); Hybrid; USD 110,000 - 150,000; Full time

Job summary

Amaze Systems is seeking a Senior Data Solutions Engineer to lead the design, development, and optimization of scalable data infrastructure and enterprise reporting. You will bridge data engineering with business intelligence, ensuring accurate, reliable data to guide decisions.

You will mentor BI developers and data engineers, fostering collaboration and continuous improvement across product teams, analytics, and reporting initiatives. Hybrid role in Edina, MN.

Qualifications

• Leadership experience guiding data teams.
• Strong ETL/ELT skills with data pipelines.
• Experience with SSRS and Power BI dashboards.
• Bonus: ML/AI exposure is a plus.
• Retail background is preferred.

Responsibilities

• Lead data engineers and BI developers to deliver scalable data solutions.
• Design, build, and maintain data pipelines and data warehouses.
• Oversee SSRS/Power BI reporting and self-service analytics standards.
• Establish data governance, validation, and quality controls.
• Collaborate with product and business stakeholders to translate requirements.

Skills

Leadership

Data Engineering

ETL/ELT

SSRS

Power BI

Data Warehousing

Data Modeling

Governance

BI & Analytics

Communication

Tools

Git

Job description

Hi,

Title: Data Engineer

Location: Hybrid 4 days onsite in Edina, MN.

Client is ideally seeking a Data Engineer with leadership qualities that comes from a retail background. Must haves include strong ETL/ELT skills, SSRS, and Power BI. Having ML and/or AI experience is a bonus.

Position Overview

The Senior Data Solutions Engineer will lead the design, development, and optimization of scalable data infrastructure and enterprise reporting solutions. This role bridges technical data engineering with actionable business intelligence, ensuring that the organization’s data assets are accurate, reliable, and strategically aligned to drive business decisions.

You will lead BI developers and Data Engineers and foster a collaborative culture of innovation, accountability, and continuous improvement across product teams, analytics and reporting initiatives.

Key Responsibilities

Leadership & Team Mentoring

• Lead, mentor, and develop a team of data engineers and BI developers.
• Communicate business priorities, define goals, and establish clear KPIs to track performance and delivery.
• Foster a collaborative and learning-oriented culture across technical and business functions.

Data Engineering

• Design, build, and maintain scalable and efficient data pipelines and integrations across multiple internal and external systems.
• Oversee ETL/ELT processes ensuring data accuracy, reliability, and timeliness.
• Manage data models and data warehouse structures optimized for reporting, analytics, and advanced use cases (e.g., predictive modeling, machine learning).
• Implement best practices in data architecture, automation, and version control (e.g., Git).

Business Intelligence & Reporting

• Oversee the design and delivery of SSRS and Power BI dashboards, ensuring usability and alignment with business goals.
• Establish and manage data visualization standards, reusable datasets, and semantic models for self-service analytics.
• Collaborate with business stakeholders to gather requirements and translate them into technical specifications and BI solutions.

Data Governance & Quality

• Implement and enforce governance policies around data definitions
• Ensure data validation, auditing, and reconciliation processes are automated and transparent.

Cross-Functional Collaboration

• Partner with product managers to align on priorities and business leaders to enable data-driven decisions.
• Communicate complex data concepts in a clear, actionable way for both technical and non-technical audiences.

Core Competencies

• Strategic Thinking: Balances short-term delivery with scalable, long-term architecture.
• Leadership: Inspires and mentors cross-functional teams, fostering accountability and curiosity.
• Analytical Agility: Translates complex data into clear insights and business recommendations.
• Collaboration: Builds strong relationships with business and technology partners.
• Execution: Delivers reliable, high-quality data solutions under tight timelines