Senior Data Engineering Consultant

About the role

This is a remote, initial 6-month engagement with strong potential for extension (12+ months anticipated based on project needs).

Key Responsibilities

• Conduct a comprehensive assessment of an existing enterprise data platform and reporting solution.
• Evaluate data ingestion processes, transformation workflows, storage architecture, semantic models, and reporting layers.
• Analyze scalability, maintainability, performance, security, supportability, and operational readiness.
• Review database architecture, data models, and reporting structures.
• Identify technical debt, architectural limitations, operational risks, and growth constraints.
• Assess alignment with enterprise architecture standards, governance requirements, and future business needs.
• Develop recommendations regarding enhancement, redesign, migration, or replacement strategies.
• Define future-state architecture and modernization roadmaps.
• Evaluate data lake and enterprise analytics integration opportunities.
• Present findings and recommendations to engineering and business stakeholders.
• Design and implement approved future-state solutions.
• Build and optimize scalable data pipelines and integration frameworks.
• Establish CI/CD pipelines, deployment automation, and DataOps best practices.
• Support data catalog, semantic layer, and data publishing initiatives.
• Collaborate with cross-functional technology and business teams.
• Improve visibility into operational metrics, service performance trends, and enterprise reporting capabilities.
• Document architecture decisions, standards, processes, and implementation approaches.
• Provide technical leadership throughout assessment, design, and implementation phases.

Required Qualifications

• Extensive senior-level Data Engineering experience.
• Data Architecture and Solution Design expertise.
• Enterprise Data Platform assessment and modernization experience.
• Strong background evaluating scalability and maintainability of existing data solutions.
• Database design and advanced data modeling experience.
• Proven ability to design and build enterprise data pipelines.
• Advanced SQL development and optimization skills.
• Experience with ETL/ELT platforms and integration solutions.
• Architecture review and future-state planning expertise.

Preferred Experience

• ServiceNow platform or development experience.
• Understanding of ServiceNow data models and reporting capabilities.
• IT Service Management (ITSM) domain knowledge.
• Experience with Incident, Change, and Problem Management reporting.
• Financial Services, Banking, Insurance, Wealth Management, or other highly regulated industries.
• Fortune 500 or large enterprise environments.
• Enterprise governance and architecture frameworks.
• Operational analytics and service management reporting initiatives.

Required Technologies

• Databricks
• SQL
• Data Lake Platforms
• GitHub
• GitHub Actions
• Jenkins
• Kubernetes
• Kafka
• Enterprise Analytics and Reporting Platforms

Nice-to-Have Technologies

• ServiceNow
• Java
• Mainframe Technologies
• Semantic Modeling Tools
• Data Catalog Solutions
• Dashboarding and Reporting Platforms
• Cloud-Based Data Engineering Technologies