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Principal Data Engineer in Germantown

Job in Germantown, Montgomery County, Maryland, 20875, USA
Listing for: Energy Jobline ZR
Full Time position
Listed on 2026-06-18
Job specializations:
  • IT/Tech
    Data Engineering
  • Engineering
    Data Engineering
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below

Job Description Job Description

Role Overview

The Principal Data Engineer is a senior technical authority responsible for defining the organization's data architecture, setting long-term technical strategy, and solving the most complex data engineering challenges. This role influences company-wide data standards, mentors senior engineers, and partners with executive and cross-functional leaders to ensure data platforms scale with the business.

Key Responsibilities
  • Define and evolve the long-term data architecture and technical vision
  • Design highly scalable, resilient data platforms and pipelines
  • Set standards for data modeling, reliability, observability, and governance
  • Lead complex, high-risk technical initiatives and migrations
  • Serve as the escalation point for critical data incidents and root cause analysis
  • Influence tool selection and technology adoption across the data stack
  • Mentor Staff and Senior Data Engineers and elevate engineering excellence
  • Partner with leadership to align data strategy with business goals
  • Ensure data platforms support analytics, ML, and product use cases at scale
Qualifications
  • Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience)
  • 10+ years of experience in data engineering or related disciplines
  • Expert-level SQL and strong proficiency in Python or similar
  • Deep experience with data warehousing, data lakes, and distributed systems
  • Proven track record of designing and operating large-scale data platforms
  • Strong systems thinking and architectural decision-making skills
Experience
  • Cloud platforms (AWS, Azure, or GCP)
  • Streaming and real-time systems (Kafka, Spark, Flink, etc.)
  • Advanced data governance, security, and compliance practices
  • Supporting ML, AI, or product-led data platforms
  • Influencing technical direction without direct managerial authority
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