Analytics & Solutions Engineer

SoTalent; West Allis (WI); Hybrid; USD 95,000 - 125,000; Full time

Job summary

Sotalent in Wisconsin is seeking a data engineer to join a hybrid team focused on transforming complex data into trusted datasets and scalable data pipelines that power business intelligence and advanced analytics.

You will define data definitions, metadata, and lineage, collaborate with stakeholders to prioritize datasets, and contribute to data governance, CI/CD practices, and agile delivery while supporting ML-ready data products.

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.

Responsibilities

• 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.
• 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.
• 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.

Skills

Python

SQL

Power Platform

CI/CD

Agile

Data Modeling

Cloud Analytics

Education

Bachelor's degree in Computer Science or related field

Tools

Power BI

Power Apps

Power Automate

Dataverse

Job description

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

• 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.
• 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.
• 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.