Analytics Engineer

Accountabilities:
The Analytics Engineer will be responsible for building and supporting enterprise analytics solutions by translating business requirements into governed, scalable data assets. The role requires strong collaboration across technical and business teams to deliver accurate reporting, improve data accessibility, and support strategic decisions. Partner with business stakeholders, department leaders, and analytics teams to understand reporting requirements, KPIs, and analytical needs, translating them into clear technical solutions. Design, develop, and maintain scalable data models, including dimensional models, star schemas, data marts, and governed analytical datasets. Build and support Power BI semantic models by creating accurate relationships, reusable calculations, business measures, and optimized reporting structures. Develop and maintain data pipelines, transformations, SQL queries, stored procedures, views, and curated datasets that convert raw information into actionable insights. Support modernization initiatives by improving reporting architecture, enhancing BI capabilities, and contributing to migration toward Microsoft Fabric and modern analytics platforms. Validate data accuracy, investigate discrepancies, document business logic, and communicate findings clearly to technical and non-technical stakeholders. Monitor reporting assets, datasets, and metrics to identify data quality issues, performance challenges, and opportunities for improvement. Create and maintain documentation covering data models, reporting definitions, source-to-target mappings, calculations, and governance practices. Promote data governance by supporting standardized definitions, metadata management, trusted data sources, and structured access to analytical assets. Integrate and analyze data from multiple sources, including APIs, databases, applications, logs, and business systems. Requirements: The ideal candidate combines strong technical expertise in analytics engineering with excellent communication skills and the ability to collaborate with diverse teams. They should be comfortable managing complex data environments while delivering practical solutions that support business objectives. Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, Applied Mathematics, or a related technical field, or equivalent practical experience. Experience designing data pipelines, curated datasets, and analytical solutions within enterprise data environments. Strong knowledge of data warehousing concepts, dimensional modeling, star schemas, data marts, and business-focused analytical models. Experience developing Power BI semantic models, including relationships, calculations, measures, and performance optimization. Advanced SQL skills with experience creating queries, views, stored procedures, scripts, and data validation solutions. Ability to gather business requirements, understand reporting needs, and translate complex requirements into effective technical implementations. Strong communication skills with the ability to explain technical concepts, data challenges, assumptions, and recommendations to different audiences. Experience collaborating with data engineering, BI, analytics, and business teams to deliver trusted reporting solutions. Strong organizational skills with the ability to manage multiple priorities, work independently, and operate effectively in a fast-paced environment. Preferred experience with Microsoft Fabric, Power BI, Dataflows, modern lakehouse or warehouse architectures, and BI platform migrations. Familiarity with data governance, metadata management, data cataloging, and reporting standardization practices is a plus. Experience developing dashboards, KPIs, and analytics solutions supporting operational, financial, sales, or service-related decisions is preferred. A master’s degree in a related technology, analytics, engineering, or business discipline is a plus. Benefits: Competitive compensation package. Remote work flexibility within the United States. 401(k) plan with employer matching contributions. Medical, dental, and vision insurance options. Health Savings Account (HSA) with employer contribution. Flexible Spending Account (FSA) options. Employer-paid life insurance and disability coverage. Paid parental leave and paid time off. Employee Assistance Program and wellness programs. Telehealth services and travel assistance benefits. Legal assistance and identity theft protection plans. Volunteer time off and paid holidays. Additional wellness, insurance, and employee support benefits.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
#LI-CL1