Senior Analytics Engineer – Financial Services

We are seeking a Senior Analytics Engineer (Manager Level) to support complex enterprise data, analytics, and reporting initiatives within a large financial services environment. This individual will serve as a hands-on technical leader, partnering with architects, business stakeholders, and technical teams to design and deliver scalable data 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 supporting reporting, analytics, and regulatory requirements.

• Build and oversee ETL/ELT pipelines, data integration workflows, and data quality controls.

• Lead technical solutioning discussions and provide guidance on analytics architecture and engineering best practices.

• Support broader data governance, enterprise reporting, and risk management initiatives.

Qualifications

• 10+ years of experience in analytics engineering, data engineering, data warehousing, or related disciplines.

• Advanced SQL expertise, including complex query development and performance optimization.

• Strong hands-on experience with dimensional modeling, data warehousing, and ETL/ELT frameworks.

• Demonstrated ability to drive technical solutioning and work effectively with architects, business leaders, and technical stakeholders.

• Experience delivering enterprise-scale analytics and reporting solutions.

• Strong communication and stakeholder management skills.

Preferred Experience

• Financial Services, Banking, Capital Markets, or Risk environments.

• Regulatory reporting, risk data aggregation, BCBS 239, or enterprise reporting initiatives.

• Cloud-based data platforms and modern analytics ecosystems.

• Consulting or professional services environments.

Ideal Candidate

A highly technical analytics engineering leader who can operate at both the architecture and hands-on engineering level. This person should be comfortable leading technical discussions, engaging directly with stakeholders, and translating complex requirements into scalable data solutions.

Deep expertise in SQL, dimensional data modeling, and ETL/ELT is more important than experience with any specific technology stack.