Principal Data Engineer - H&B Data & Analytics Platform

WTW is a company that helps clients control health and welfare plan costs and improve health outcomes. They are seeking a Principal Data Engineer to design and build scalable data platforms that support analytics and advanced AI use cases, while also mentoring engineering teams and driving platform modernization.

Responsibilities:

• Lead the design and evolution of enterprise‑scale data platforms, including ingestion, transformation, storage, and consumption layers
• Define and enforce data engineering standards, patterns, and best practices (e.g., pipeline design, testing, CI/CD, observability)
• Serve as a technical authority on data architecture decisions, trade‑offs, and platform strategy
• Design, build, and optimize high‑performance batch and streaming data pipelines
• Improve reliability, performance, scalability, and cost efficiency of existing data assets
• Implement reusable frameworks and reference architectures to accelerate delivery across teams
• Design and operate Databricks‑based lakehouse solutions using Delta Lake, Spark, and notebooks/jobs
• Establish best practices for Databricks workspace architecture, security, performance tuning, and cost management
• Lead or support migrations to Databricks and modernization of legacy data pipelines
• Partner with data governance and security teams to embed data quality checks, metadata, lineage, and access controls into pipelines
• Ensure platforms support regulatory, compliance, and enterprise risk requirements
• Work closely with data architects, analytic engineers, data scientists, product owners, and business stakeholders
• Translate business and analytic requirements into scalable technical solutions
• Influence roadmaps by tying platform investments to measurable business outcomes
• Mentor senior and mid‑level engineers; raise the overall technical bar of the team
• Lead by example through hands‑on contribution to critical pipelines and platform components

Requirements:

• University or college degree in Computer Science, Information Systems, Mathematics, Engineering, Statistics, or related field of study
• 8+ years of experience in data engineering or platform engineering roles
• Deep expertise in building large-scale data pipelines and platforms in cloud environments (Azure, AWS, or GCP)
• Strong proficiency with distributed data processing (e.g., Spark)
• Advanced SQL and strong Python programming skills
• Experience designing data models and architectures for analytics and downstream consumption
• Strong analytical skills and experience with data modeling
• Strong project management and organizational skills
• Proven ability to work independently and with a team
• Prior experience setting engineering standards or leading platform modernization initiatives
• Experience in data ingestion tools such as Matillion, FiveTran, Airbyte, etc
• Extensive hands-on experience with Databricks and Lakehouse architecture strongly preferred
• Experience with Delta Lake, Spark optimization, and cost/performance tuning strongly preferred
• Experience supporting advanced analytics, machine learning, or AI-driven use cases
• Familiarity with modern data tooling (e.g., orchestration, data quality frameworks, metadata/catalog tools)