Principal Data Warehouse Engineer - Executive Director

Join us and bring your innovative spirit to a team where your expertise shapes the future of data engineering. As a Principal Data Engineer, you will inspire change and deliver solutions that make a lasting impact. We value visionary leadership, collaboration, and a commitment to excellence. You’ll have the opportunity to grow your career, work with talented colleagues, and contribute to a culture of inclusion and respect. Your contributions will help us push the limits of what’s possible.

Job Summary:
As a Principal Data Engineer in Enterprise Technology, Infrastructure Platforms team, you will provide data engineering excellence as an integral part of an agile team. You will enhance, build, and deliver data collection, storage, access, and analytic solutions in a secure, stable, and scalable way. Leveraging your advanced technical capabilities, you will collaborate across the organization to drive best-in-class outcomes for various data pipelines and architectures. Your role will support one or more of the firm’s portfolios, helping shape the team culture and the impact of our work.

Job Responsibilities:

• Partner proactively with principal architects to transform design intent into practical delivery roadmaps.
• Design, build, and optimize complex data warehouse solutions for scalability, reliability, and performance.
• Develop and implement robust data pipelines and ETL processes to deliver secure and stable data architectures.
• Apply advanced data modeling techniques to solve business challenges and drive actionable insights.
• Collaborate with cross-functional teams to integrate data solutions into business-critical applications.
• Evaluate and select data visualization tools, creating impactful visualizations for stakeholders.
• Provide technical mentorship to junior engineers, sharing best practices and fostering continuous learning.
• Champion a culture of diversity, opportunity, inclusion, and respect in daily interactions and project work. 
• Uses enterprise-authorized AI capabilities within the work environment to accelerate data architecture and model analysis and decisioning, validating outputs and handling data according to sensitivity and security requirements.
• Leads reuse-first adoption of AI-assisted validation and documentation practices across delivery routines, ensuring traceability/auditability and alignment to resiliency and security expectations

Required Qualifications, Capabilities, and Skills:

• Expertise in data engineering, designing, building, and delivering large-scale data warehouse solutions in enterprise environments.
• Ability to apply new methods to solve complex technology problems in technical disciplines.
• Proven track record of leading end-to-end delivery of data pipelines, ETL processes, and data architecture projects.
• Experience leading products as a Principal Engineer or Technical Delivery Lead.
• Ability to present and communicate technical concepts, project progress, and solution impacts to senior leaders.
• Experience with emerging technologies and best practices, focusing on practical implementation and integration.
• Proficient understanding of existing and new data management systems, with a commitment to continuous learning.
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support advanced data engineering workflows with strong validation habits and awareness of data sensitivity.
• Ability to review and validate AI-assisted outputs and recommendations before adoption, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations.
• Strong proficiency in hands-on development using industry-standard tools and languages (e.g., SQL, Python, Spark, cloud platforms).

Preferred Qualifications, Capabilities, and Skills:

• Hands-on experience with Databricks and proficiency in managing large datasets using Apache Iceberg.
• Experience architecting and implementing enterprise-scale data warehouses on cloud platforms (e.g., AWS, Azure, GCP).
• Advanced proficiency in designing and optimizing data models for analytics, reporting, and business intelligence.
• Ability to automate data pipeline deployment and monitoring using CI/CD tools and infrastructure-as-code practices.
• Expertise with distributed data processing frameworks (e.g., Apache Spark, Hadoop) and real-time data streaming technologies (e.g., Kafka, Kinesis, Spark).
• Experience collaborating with cross-functional teams to deliver impactful data solutions.
• Ability to evaluate, select, and integrate emerging data technologies and tools for scalability, security, and performance.
• Published contributions to open-source projects, technical blogs, or industry forums related to data engineering.
• Advanced degree in Computer Science, Engineering, Mathematics, or a related field.
• Recognized for mentoring and developing technical talent, fostering innovation and continuous improvement.