Data Engineer, Consultant
About The Position
The Data Engineer, Consultant is a senior individual contributor and technical leader on the Data Services team, which designs and delivers complex, data-driven solutions and data products for the enterprise. Reporting to the Sr Manager, Data Solutions / Manager, this role drives end-to-end delivery of data engineering solutions across cloud data platforms. The position partners with Solution Design Leads, Architects, Product Managers, and business stakeholders to turn solution designs and business requirements into scalable, secure, production-ready data products. The role also provides technical leadership and mentorship to Data Engineers and Senior Data Engineers without formal people-management responsibility. It works within an agile / DevSecOps pod model and supports the integration of AI/ML-ready datasets by ensuring data is well-modeled, reliable, and governed. The workplace model emphasizes purposeful in-person collaboration and flexibility. Most teams are expected to work from the office two days per week; arrangements for certain employees may depend on business needs. The work is based in an office and home-office/deskwork environment, with a sedentary activity level for most of the workday.
Requirements
- Bachelor's degree or equivalent experience.
- Minimum of 7 years of data engineering experience.
- Advanced hands-on expertise in SQL, including automation and pipeline optimization.
- Strong experience with cloud platforms, preferably Azure, and services such as ADLS, Synapse, and Data Factory.
- Extensive experience with modern data platforms including Snowflake and 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 large-scale, distributed data platforms and parallel processing architecture.
- Excellent communication and stakeholder engagement skills.
- Proven ability to lead technically without formal people-management responsibility.
Nice To Haves
- Healthcare industry experience, including exposure to Epic or similar ecosystems.
Responsibilities
- 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, including Data Vault 2.0, dimensional, and domain-oriented models, to support analytics and reporting.
- Embed data quality, testing, security, and observability by design across data pipelines.
- Drive operational excellence through incident analysis, stabilization, performance tuning, and deployment optimization.
- Identify and implement opportunities to optimize performance, reliability, and cloud costs.
- 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 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 technical and non-technical stakeholders.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
