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Open nowPosted 26 hours ago

Senior Principal Database Engineer

Jobgether4,233 open roles

Where
US
Work mode
Remote
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Your applicationOpen nowSenior Principal Database EngineerJobgether · US

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Jobgether's own form.

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The clock on this job

Early applications get read.

7.8% of postings close within 7 days. Measured by our own scanner across the market. Jobgether postings stay open a median of 4 days.

Share of postings closed within
  1. 1.7%1 day
  2. 3.5%3 days
  3. 7.8%7 days
  4. 14.6%14 days
  5. 34.1%30 days
This job: posted 26 hours ago

Jobgether median: 4 days open

The posting

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Principal Database Engineer based in the United States.

This role provides senior technical leadership in designing and evolving modern data platforms that power enterprise analytics, reporting, machine learning, and AI initiatives. You’ll architect scalable data solutions, build high-performance pipelines, and establish secure, governed foundations for critical data products. The position combines deep expertise in cloud data engineering with hands-on development, infrastructure automation, and platform optimization. You’ll work closely with business stakeholders, data scientists, analysts, architects, and engineering teams to translate complex requirements into reliable technical solutions. You’ll also influence architecture decisions, introduce emerging technologies, and improve platform performance, reliability, and cost efficiency. As a senior technical leader, you’ll mentor engineers and help establish engineering standards across large-scale, collaborative Agile environments.

Accountabilities:

  • Design, build, and optimize enterprise-scale data platforms, lakehouse architectures, data models, and analytics solutions.
  • Develop and maintain scalable ETL/ELT pipelines using SQL, Python, PySpark, and distributed data processing technologies.
  • Architect secure, reliable, and cost-efficient cloud data environments across AWS, Snowflake, Azure, Databricks, and other cloud platforms.
  • Implement data quality, monitoring, governance, security, identity, and access-control frameworks across data platforms.
  • Automate cloud infrastructure provisioning and platform operations using Infrastructure-as-Code tools such as Terraform.
  • Develop CI/CD pipelines, deployment automation, monitoring capabilities, and operational processes that improve platform reliability.
  • Partner with business stakeholders and technical teams to gather requirements, troubleshoot complex issues, and translate business needs into scalable solutions.
  • Lead technical initiatives and influence architectural decisions while advising teams on data engineering and platform best practices.
  • Evaluate and introduce emerging technologies, including machine learning, MLOps, GenAI, LLMs, and AI-powered automation solutions.
  • Support cloud migration initiatives, including transitions from on-premises environments to modern cloud lakehouse architectures.
  • Optimize cloud spending, platform performance, scalability, and operational efficiency across high-volume enterprise workloads.
  • Mentor engineers, conduct code reviews, establish engineering standards, and contribute to a culture of continuous technical improvement.
  • Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related technical discipline, or an equivalent combination of education and relevant experience.
  • Master’s degree in Computer Science, Information Systems, Data Science, or a related field is preferred.
  • 10+ years of progressive experience in data engineering, analytics engineering, business intelligence, or related technical roles.
  • Proven experience designing and delivering enterprise-scale data platforms and analytics solutions.
  • Advanced proficiency in SQL and Python, with strong hands-on experience using PySpark and distributed data processing.
  • Strong understanding of data warehousing, data lakes, lakehouse architectures, enterprise data modeling, and modern data platforms.
  • Experience building and maintaining scalable ETL/ELT pipelines and implementing data quality, monitoring, and governance frameworks.
  • Hands-on experience with AWS services such as S3, IAM, Glue, and Lake Formation.
  • Experience with Snowflake, Databricks, Azure, GCP, or other modern cloud data platforms, with enterprise Snowflake administration and scaling experience preferred.
  • Strong knowledge of secure cloud-native architectures, cloud security, identity management, and access controls.
  • Experience with Terraform or comparable Infrastructure-as-Code technologies, Git-based development, CI/CD, and deployment automation.
  • Experience working with Agile methodologies such as Scrum, Kanban, or SAFe in highly collaborative environments.
  • Strong communication, documentation, stakeholder management, and problem-solving skills, with the ability to work effectively with technical and non-technical audiences.
  • Ability to independently drive initiatives from concept through implementation and ongoing support.
  • Experience supporting machine learning, MLOps, AI-enabled analytics, GenAI, or LLM-based solutions is preferred.
  • Familiarity with dbt, Tableau or other business intelligence tools, cloud migration, platform governance, and cloud cost-management strategies is a plus.
  • Experience mentoring engineers, conducting code reviews, establishing technical standards, and supporting high-volume enterprise data environments is preferred.
  • Relevant certifications such as Databricks Certified Data Engineer, AWS certifications, Snowflake certifications, Azure Data Engineer Associate, or Terraform Associate are preferred.
  • Expected annual base salary of $131,000–$180,000, depending on geographic market, skills, experience, education, and other applicable factors.
  • Medical, dental, and vision coverage.
  • Health Savings Account (HSA) and Flexible Spending Account (FSA) options.
  • Life and AD&D insurance.
  • 401(k) retirement benefits.
  • Tuition reimbursement.
  • Resources and programs supporting long-term health and well-being.
  • Fully remote position available anywhere in the United States.
  • Opportunity to work on enterprise-scale data, cloud, machine learning, and AI initiatives.
  • Collaborative environment focused on innovation, continuous improvement, technical growth, and professional development.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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