Data Engineer IV

Description *Due to NERC regulations US Citizenship, Green Card Hold, or Permanent Residency is required for this role.* Northwind Robotics is partnered with an established client to fill a remote Data Engineer IV position on a team we have successfully supported for a few years. This is hands-on engineering position requiring the ability evaluate execution layer code. Data Engineer IV Position Summary 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. Basic 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. Originally posted on Himalayas