Analytics & Solutions Engineer

Analytics & Solutions Engineer

Location: West Allis, WI, US

Industry: Business Consulting and Services

Work Setting: Hybrid

Are you passionate about transforming complex data into actionable insights, building scalable analytics solutions, and driving data-driven decision-making across an organization? Join a high-impact data engineering and analytics team where you'll design data products, develop modern data pipelines, and enable trusted, high-quality data that powers business intelligence, advanced analytics, and machine learning initiatives.

What You'll Do

Data Engineering & Data Product Development

• Lead the acquisition, integration, transformation, and structuring of data from multiple sources to create high-quality datasets for analytical consumption.
• Design, develop, and maintain scalable data products that support business intelligence, analytics, reporting, and machine learning initiatives.
• Establish clear data definitions, metadata, lineage, and source-of-truth standards to ensure data consistency and trust.
• Collaborate with stakeholders to identify and prioritize valuable datasets that support business objectives.

Analytics & Data Solutions

• Partner with business users, analysts, and data consumers to understand requirements and deliver impactful data solutions.
• Develop data models and structures optimized for reporting, analytics, and predictive modeling.
• Create scalable solutions that enable self-service analytics and enterprise-wide data accessibility.
• Support advanced analytics and machine learning use cases by preparing reliable and consumable datasets.

Cloud Data Engineering

• Build and maintain cloud-based data platforms, pipelines, and analytics environments.
• Design and optimize ETL/ELT workflows for large-scale data processing and integration.
• Work with distributed data systems, data lakes, and modern cloud analytics technologies.
• Implement best practices for data storage, partitioning, performance optimization, and scalability.

Software Engineering & DevOps

• Apply modern engineering principles throughout the development lifecycle, including design, testing, deployment, and support.
• Utilize CI/CD methodologies and automation practices to ensure reliable and efficient delivery of data products.
• Participate in Agile ceremonies, including story refinement, sprint planning, estimation, and demonstrations.
• Lead code reviews and promote engineering standards focused on quality, maintainability, and performance.

Data Quality & Governance

• Design and implement data validation, testing, and quality assurance processes.
• Ensure accuracy, consistency, and reliability across enterprise data assets.
• Support governance initiatives related to data integrity, privacy, security, and regulatory compliance.
• Promote a single source of truth through standardized data flows and enterprise data management practices.

Leadership & Mentorship

• Provide technical leadership and thought partnership within Agile teams.
• Mentor junior engineers and support their technical and professional development.
• Guide design decisions, development standards, and best practices across projects.
• Translate complex technical concepts into clear business language for stakeholders at all levels.

What We're Looking For

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, Analytics, Mathematics, or a related field.
• 4+ years of experience in data engineering, analytics engineering, data development, or a related discipline.
• Strong experience acquiring, transforming, cleansing, and preparing data for analytics and reporting purposes.
• Expertise designing and developing solutions using Microsoft Power Platform technologies, including Power BI, Power Apps, Power Automate, Dataverse, and related services.
• Strong Python programming skills and experience building data processing solutions.
• Advanced SQL expertise, including data modeling, optimization, and ETL development.
• Experience working with cloud-based analytics and data platforms.
• Deep understanding of data lake architectures and distributed data systems.
• Experience implementing CI/CD practices and Agile development methodologies.
• Strong analytical, troubleshooting, and problem-solving capabilities.

Preferred Qualifications

• Experience working with cloud analytics technologies, data warehouses, and modern data platforms.
• Expertise in dimensional and relational data modeling techniques.
• Experience supporting analytics, machine learning, and data science environments.
• Knowledge of business intelligence platforms and data visualization tools.
• Experience in DevOps-driven delivery environments.
• Consulting or customer-facing analytics experience.
• Familiarity with regulatory and privacy requirements governing sensitive data.
• Experience working with large-scale enterprise data ecosystems.