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Open nowFirst seen 35 hours ago

Data Engineer IV (Remote)

roiagency/ca.00a58 open roles

Where
Spokane, WA (Remote), Remote
Work mode
Remote
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Your applicationOpen nowData Engineer IV (Remote)roiagency/ca.00a · Spokane, WA (Remote), Remote

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The clock on this job

Early applications get read.

15.1% of postings close within 7 days. Measured by our own scanner across the market. roiagency/ca.00a postings stay open a median of 1 days.

Share of postings closed within
  1. 2.4%1 day
  2. 6.5%3 days
  3. 15.1%7 days
This job: first seen 35 hours ago

roiagency/ca.00a median: 1 days open

The posting

*Due to NERC regulations US Citizenship, Green Card Hold, or Permanent Residency is required for this role.*

ROI Agency 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.
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