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# Principal Data Engineer in Germantown

- **Company:** Energy Jobline
- **Location:** Germantown, MD, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Data Architecture, Information Engineering, Data Governance, Data Warehousing, Python (Programming Language), SQL Databases, Data Streaming, Real Time Systems, Apache Spark, Data Strategy, Data Lakes, Information Technology, Apache Flink, Apache Kafka, Data Management
- **Published:** September 4, 2026
- **Apply:** https://www.energyjobline.com/job/principal-data-engineer-germantown-31510209

## About the Role

platforms support analytics, ML, and product use cases at scaleQualificationsBachelor's degree in Computer Science, Engineering, or related field (or equivalent experience)10+ years of experience in data engineering or related disciplinesExpert-level SQL and strong proficiency in Python or similar languagesDeep experience with data warehousing, data lakes, and distributed systemsProven track record of designing and operating large-scale data platformsStrong systems thinking and architectural decision-making skillsPreferred ExperienceCloud platforms (AWS, Azure, or GCP)Streaming and real-time systems (Kafka, Spark, Flink, etc.)Advanced data governance, security, and compliance practicesSupporting ML, AI, or product-led data platformsInfluencing technical direction without direct managerial authority

## Description

Role OverviewThe 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 ResponsibilitiesDefine and evolve the long-term data architecture and technical visionDesign highly scalable, resilient data platforms and pipelinesSet standards for data modeling, reliability, observability, and governanceLead complex, high-risk technical initiatives and migrationsServe as the escalation point for critical data incidents and root cause analysisInfluence tool selection and technology adoption across the data stackMentor Staff and Senior Data Engineers and elevate engineering excellencePartner with leadership to align data strategy with business goalsEnsure data


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