Senior Analytics Engineer [Remote]

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Analytics Engineer based in the United States.

In this role, you will play a key part in shaping a modern, AI-ready data ecosystem that powers analytics, business intelligence, and machine learning across the organization. You will design and maintain scalable data models and semantic layers that serve as the single source of truth for core business metrics. Working in a highly collaborative environment, you will partner with Data Engineering, Data Science, Product, and DevOps teams to transform raw data into reliable, actionable insights. Your work will directly support predictive modeling, real-time analytics, and AI-driven applications that influence strategic decision-making. This is a hands-on, high-impact position where data quality, governance, and scalability are central to success. You will help define how data is structured, trusted, and consumed across the business, enabling both human and AI systems to make better decisions.

Accountabilities:

You will be responsible for building and maintaining the foundational data models, metrics, and pipelines that power analytics and AI use cases across the organization. You will ensure that data is accurate, well-structured, and accessible for downstream consumers, while continuously improving scalability and governance. Key responsibilities include:

• Design and develop scalable dimensional data models and data marts using dbt
• Build and maintain a robust semantic and metrics layer to standardize business KPIs across dashboards, analytics, and AI-driven applications
• Contribute to the development of an AI-ready data foundation supporting advanced use cases such as predictive modeling and agent-based systems
• Collaborate with Data Engineering, Data Science, BI, Product, and DevOps teams to unify data sources and eliminate fragmented logic
• Translate business requirements into reliable, production-ready data models and transformation pipelines
• Support data science workflows by delivering structured, validated features for training and inference models
• Partner with engineering teams to ensure accurate data integration during schema changes, migrations, and system updates
• Contribute to real-time and batch data pipelines, ensuring reliability, performance, and observability
• Review code contributions, mentor peers, and enforce best practices in data modeling, testing, and documentation
• Strengthen data governance through testing frameworks, lineage tracking, cataloging, and quality controls

Requirements

The ideal candidate brings strong analytics engineering experience combined with deep SQL expertise and a proven ability to build scalable, production-grade data systems. You are comfortable working across technical and business teams to translate complex needs into structured data solutions. Key qualifications include:

• 4+ years of experience in Analytics Engineering, Data Engineering, or Business Intelligence roles
• 2+ years of hands-on experience building production data pipelines using dbt or similar tools
• 2+ years of experience working with cloud data warehouses such as Snowflake or Amazon Redshift
• Advanced SQL skills with strong expertise in dimensional data modeling and analytics engineering best practices
• Experience building reliable, tested, and scalable data models used across multiple stakeholders and systems
• Ability to translate ambiguous business requirements into structured, maintainable data solutions
• Strong collaboration and communication skills, with experience working in cross-functional technical teams
• Experience with Python for data transformation, automation, or analytics is a plus
• Familiarity with semantic/metrics layers, data governance, or AI/ML-enabled data products is highly desirable
• Experience in fintech, lending, or other data-intensive industries is a plus

Benefits

• Competitive annual compensation ranging from $145,000 to $170,000 USD plus a 10% target bonus
• Fully remote work flexibility within the United States
• Performance-based bonus structure aligned with company success
• Comprehensive healthcare coverage and benefits package
• Career growth opportunities in a fast-scaling, data-driven organization
• Exposure to advanced analytics, AI, and machine learning initiatives
• Collaborative, high-impact environment with cross-functional teams
• Ongoing learning and development opportunities
• Competitive, market-aligned compensation with regular benchmarking.

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!

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

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.