Data Engineer, Consultant

The Data Services team is responsible for technical design and end-to-end delivery of complex data-driven solutions and data products for the enterprise. The Data Engineer,Consultant will report to the Sr Manager, Data Solutions / Manager. This role serves as a senior individual contributor and technical leader, responsible for driving end-to-end delivery of complex data engineering solutions across cloud data platforms. The DE-C partners closely with Solution Design Leads, Architects, Product Managers, and business stakeholders to translate solution designs and business requirements into scalable, secure, and production-ready data products., * Lead the design and implementation of complex, data pipelines and data products from development through production

• Translate solution designs and business requirements into detailed technical architecture and implementation plans
• Architect and build scalable, secure, and highly available data solutions across enterprise data platforms
• Apply advanced data modeling techniques (Data Vault 2.0, dimensional, and domain-oriented models) to support analytics and reporting needs
• Embed data quality, testing, security, and observability by design across data pipelines
• Drive operational excellence, including incident analysis, stabilization, performance tuning, and deployment optimization
• Identify and implement optimization opportunities related to performance, reliability, and cloud cost management
• Influence and evolve data engineering standards, patterns, and frameworks used by delivery teams
• Provide technical leadership and mentorship to Data Engineers and Senior Data Engineers through design reviews and code reviews
• Work within an agile / DevSecOps pod model, collaborating closely with solution leads, data modelers, analysts, and business partners
• Support integration of AI/ML-ready datasets by ensuring data is well-modeled, reliable, and governed
• Communicate complex technical concepts clearly to both technical and non-technical stakeholders

Your Work

In this role, you will:

• Lead the design and implementation of complex, data pipelines and data products from development through production
• Translate solution designs and business requirements into detailed technical architecture and implementation plans
• Architect and build scalable, secure, and highly available data solutions across enterprise data platforms
• Apply advanced data modeling techniques (Data Vault 2.0, dimensional, and domain-oriented models) to support analytics and reporting needs
• Embed data quality, testing, security, and observability by design across data pipelines
• Drive operational excellence, including incident analysis, stabilization, performance tuning, and deployment optimization
• Identify and implement optimization opportunities related to performance, reliability, and cloud cost management
• Influence and evolve data engineering standards, patterns, and frameworks used by delivery teams
• Provide technical leadership and mentorship to Data Engineers and Senior Data Engineers through design reviews and code reviews
• Work within an agile / DevSecOps pod model, collaborating closely with solution leads, data modelers, analysts, and business partners
• Support integration of AI/ML-ready datasets by ensuring data is well-modeled, reliable, and governed
• Communicate complex technical concepts clearly to both technical and non-technical stakeholders

Consulting, Technical/Engineering Design, Software Engineering, Cloud Computing, Technical Leadership, Consulting, Multiplatform/Cross-Platform, Leadership, SQL (Structured Query Language), Automation, * Requires a bachelor’’s degree or equivalent experience.

• Requires a minimum of 7 years of data engineering experience.
• Advanced hands-on expertise in SQL, including automation and pipeline optimization
• Strong experience with cloud platforms (Azure preferred) and services such as ADLS, Synapse, and Data Factory
• Extensive experience with modern data platforms including Snowflake, Databricks, and orchestration tools such as Airflow or Tidal
• Deep understanding of data modeling, integration patterns, data architecture, data quality, and data warehousing
• Proven experience implementing CI/CD pipelines, Infrastructure as Code, and DataOps practices
• Strong understanding of security, privacy, and compliance requirements in regulated environments
• Experience working with largescale, distributed data platforms and parallel processing architecture
• Excellent communication and stakeholder engagement skills
• Proven ability to lead technically without formal people management responsibility
• Preferred: Healthcare industry experience, including exposure to Epic or similar ecosystems