Remote Senior Analytics Engineer: Lead Data Solutions

INSPYR Solutions; Davenport (IA); On-site; USD 83,000 - 96,000; Full time

Job summary

INSPYR Solutions is seeking a Senior Analytics Engineer (Manager Level) to lead enterprise data and analytics initiatives within a financial services context. This remote role partners with architects, stakeholders, and engineering teams to design scalable data solutions.

The ideal candidate has 10+ years in analytics or data warehousing, deep SQL, and hands-on experience with dimensional modeling, ETL/ELT, and data governance. Strong communication is essential.

Qualifications

• 10+ years of experience in analytics engineering, data engineering, or data warehousing.
• Advanced SQL expertise with complex query development and optimization.
• Hands-on experience with dimensional modeling, data warehousing, and ETL/ELT frameworks.
• Ability to drive technical solutioning and collaborate with architects and business leaders.
• Experience delivering enterprise-scale analytics and reporting solutions.

Responsibilities

• Lead solution design and delivery for enterprise data and analytics initiatives.
• Partner with architects, business stakeholders, and technical teams to develop scalable data solutions.
• Design and optimize dimensional data models for reporting and regulatory needs.
• Build and oversee ETL/ELT pipelines, data integration workflows, and data quality controls.
• Lead technical discussions and guide analytics architecture and engineering best practices.
• Support data governance, enterprise reporting, and risk management initiatives.

Skills

SQL

Analytics Engineering

Dimensional Modeling

ETL/ELT

Data Warehousing

Stakeholder Management

Job description

INSPYR Solutions is seeking a Senior Analytics Engineer (Manager Level) to lead enterprise data and analytics initiatives within a financial services context. This remote role partners with architects, stakeholders, and engineering teams to design scalable data solutions.

The ideal candidate has 10+ years in analytics or data warehousing, deep SQL, and hands-on experience with dimensional modeling, ETL/ELT, and data governance. Strong communication is essential.