Your Role
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,Principal will report to the Sr Manager, Data Solutions / Director. In this role you will be partnering with Enterprise Architects, Portfolio, Analytics and Data engineering teams for designing technical solutions and building data products to meet enterprise data needs. You will be responsible for driving the data product by designing and implementing cloud data lakes, data warehouse and data mart solutions.
Our leadership model is about developing great leaders at all levels and creating opportunities for our people to grow – personally, professionally, and financially. We are looking for leaders that are energized by creative and critical thinking, building and sustaining high-performing teams, getting results the right way, and fostering continuous learning.
Your Work
In this role, you will:
- Lead the design, development, and implementation of scalable data pipelines supporting enterprise data lakes, data warehouses, and data marts.
- Engineer robust ELT/ETL solutions that ingest, process, and curate structured and semi‑structured data from diverse internal and external sources.
- Apply advanced data modeling techniques (including Data Vault 2.0, dimensional, and domain‑oriented models) to support analytics and data products.
- Partner with Solution Design, Architecture, and Product teams to ensure technical designs are implemented accurately, efficiently, and securely.
- Build and optimize data solutions on cloud platforms (e.g., Snowflake, Databricks, Synapse) with a focus on performance, scalability, reliability, and cost efficiency.
- Implement data quality, validation, observability, lineage, and governance controls embedded directly into data pipelines.
- Champion and apply DevOps and DataOps best practices, including CI/CD, automated testing, infrastructure as code, monitoring, and alerting.
- Provide hands‑on technical leadership and mentorship to senior and mid‑level data engineers, promoting engineering standards and best practices.
- Collaborate using agile methodologies to plan work, refine technical stories, and deliver iteratively with predictable outcomes.
- Identify performance bottlenecks, reliability risks, and optimization opportunities across data platforms and workflows.
- Support integration of AI/ML‑ready data assets, ensuring data is trustworthy, well‑modeled, and accessible for advanced analytics use cases.
- Act as a technical thought leader, advocating for modern data engineering patterns, tools, and practices aligned to enterprise strategy.
