Data Engineer IV

Role Description

The Principal Data Engineer / Architect (Data Engineer IV) is a senior technical leader responsible for defining the enterprise-wide data architecture, platform strategy, and governance standards. This role shapes how data is collected, modeled, processed, secured, and consumed across all applications and business domains, ensuring the long-term scalability, reliability, and performance of the organization’s data ecosystem.

Principal Data Engineers drive large-scale modernization, lakehouse and warehouse architecture, MDM adoption, metadata automation, Delta Lake strategy, multi-cloud integrations, and end-to-end data platform evolution. Operating with full autonomy, this role engages with Directors, senior architects, and cross-functional leaders to guide decisions that impact enterprise systems, analytics, compliance, and technology investments.

This position is both strategic and hands-on when needed—solving the hardest technical problems, creating reusable frameworks, and mentoring senior engineers to elevate overall data engineering maturity across the enterprise.

Essential Functions:

• Own the long-term design and architecture of the enterprise data ecosystem, including ingestion, storage, modeling, lineage, governance, and analytics layers.
• Design scalable lakehouse, Delta Lake, and distributed data architectures supporting advanced analytics, operational workflows, and integration across business domains.
• Lead enterprise-wide modernization projects: warehouse migrations, domain modeling redesigns, governance uplift, streaming adoption, or cross-cloud data integrations.
• Define and enforce standards for data modeling, lineage, metadata, MDM, quality, security, and compliance across all data teams.
• Create reusable architectural patterns, frameworks, orchestrations, and platform components adopted across engineering groups.
• Solve the most complex technical problems, including distributed system bottlenecks, data quality crises, lineage gaps, and multi-domain data reconciliation issues.
• Guide cost optimization strategy for compute, storage, and orchestration workloads across the data platform.
• Partner with enterprise architecture, analytics, InfoSec, product, and application engineering to ensure alignment with organizational strategy.
• Influence leadership decisions regarding data strategy, platform investments, tooling, and sprint/roadmap priorities.
• Mentor senior engineers, conduct design reviews, and provide technical leadership across teams to raise the overall engineering bar.

Qualifications

• Bachelor’s degree in CS/IT/Data Science or equivalent experience (Master’s preferred).
• 10+ years experience in data engineering, data architecture, or distributed systems engineering.
• Proven track record designing and implementing enterprise-scale data platforms with Lakehouse/Delta architectures.
• Expert-level proficiency with SQL, Spark, Python, Databricks, Delta Lake, Azure Data Factory, and distributed processing.
• Deep understanding of data modeling (conceptual, logical, physical), governance frameworks, MDM, metadata catalogs, and lineage systems.
• Experience leading multi-team engineering initiatives and influencing architectural decisions at the leadership level.
• Strong grounding in security, compliance, data privacy, and regulatory data handling.

Company Description