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# Principal Data Engineer - Parametric

- **Company:** Morgan Stanley
- **Location:** Seattle, WA, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $115,000.0 - $225,000.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Amazon S3, Computing Platforms, Cloud Computing, Cloud Engineering, Databases, Data Architecture, Information Engineering, Data Governance, Data Structures, Data Systems, Disaster Recovery, Distributed Systems, Identity and Access Management, Machine Learning, Microsoft SQL Server, Object-Oriented Software Development, Open Source Technology, Performance Tuning, Scrum Methodology, Query Optimization, Zero Trust Network Access, Runbook, Software Engineering, SQL Server Reporting Services, SQL Server Integration Services, Snowflake, Containerization, Information Technology, Integration Frameworks, Video Streaming, Amazon Simple Queue Service (SQS), Data Pipelines, Serverless Computing, Service Stack, Legacy Systems
- **Published:** May 21, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=7d0b61b80e7ea195

## About the Role

Do you have experience in Technical writing?, * Bachelor's in Computer Science, Mathematics, or Engineering or equivalent work experience

 * 10+ years of data engineering, data science, or software engineering experience
 * 3+ years of experience with Snowflake
 * 4+ years of experience in AWS (or similar cloud technologies) cloud stack including S3, IAM, Athena, SNS, SQS, and EMR.
 * 6+ years of SQL Server and experience with tools such as SSIS and SSRS
 * Demonstrated success providing both expert technical guidance and team leadership
 * Capability of architecting highly scalable distributed systems, using different open-source tools
 * Highly skilled in leading teams using Agile development process such as Kanban or Scrum
 * Demonstrated experience with object-oriented design, coding and testing patterns as well as experience in engineering (commercial or open source) software platforms and data infrastructures
 * Expert knowledge of data modeling and understanding of different data structures and their benefits and limitations under particular use cases
 * Ability to collaborate and partner across a diverse team
 * Ability to create strong work ethics and committed teams, foster open dialogue, and promote individual and team successFinancial industry data fluency is preferred but not required

Parametric believes each member of our organization makes a significant contribution to our success. That contribution should not be limited by the assigned responsibilities. Therefore, this job description is designed to outline primary duties and qualifications. It is our expectation that every member of our team will offer his/her/their services wherever and whenever necessary to ensure the success of our

## Description

The Data Engineering team ensures that data pipelines are scalable, repeatable, secure, and can serve multiple users. We help facilitate getting data from a variety of different sources, getting it in the right formats, assuring that it adheres to data quality standards, and assuring that downstream users can get that data quickly., The Principal Data Engineer will serve as a technical lead on new and ongoing development projects, designing, developing, and maintaining services to support various business needs. In this role you will be responsible for guiding and mentoring a team of data engineers helping them to achieve their highest potential while collectively advancing the goals and projects of the engineering team.

The Principal Data Engineer is responsible for the design, structure, and maintenance of data projects ensuring the accuracy and accessibility of data relevant to an organization or a project. In this role the Principal Data Engineer needs to be able to take business requirements and design and architecture end to end that fully supports the business needs. The Lead Data engineer needs to be an expert in writing and optimizing SQL queries. They need to be able to document ideas and proposals which will include creating ER diagrams and architectural documents that document the transformation of data throughout its lifecycle.

A successful Principal Data Engineer must possess superior analytical skills and be detail-oriented. This role requires the ability to communicate effectively as part of a larger team within the information technology department. Additionally, you will need to explain complex technical concepts to non-technical staff. Since development of data models and logical workflows is common, a Principal Data Engineer must also exhibit advanced visualization skills, as well as creative problem-solving.

PRIMARY RESPONSIBILITIES

 * AI & Automation Integration: Design and implement data pipelines optimized for machine learning, generative AI, and real-time analytics.
 * Modern Data Architecture: Build scalable, cloud-native architectures leveraging Data Mesh, Lakehouse, and streaming technologies.
 * Data Governance & Ethics: Enforce responsible AI practices, data privacy, and compliance with evolving regulations.
 * Performance Optimization: Apply advanced techniques for query optimization, distributed computing, and cost-efficient cloud operations.
 * Legacy Modernization: Reimagine legacy systems using containerization, serverless computing, and AI-driven orchestration.
 * Collaboration & Leadership: Partner with business and technical stakeholders to align solutions with strategic objectives.
 * Documentation & Standards: Maintain technical specifications, runbooks, and architectural diagrams.
 * Security & Resilience: Implement zero-trust security models, disaster recovery, and automated failover strategies.
 * Continuous Innovation: Evaluate emerging technologies (e.g., AI agents, quantum-ready data frameworks) and integrate where applicable.
 * Evaluates and provides feedback on future technologies and new releases/upgrades.
 * Contributes to the establishment of business continuity & disaster recovery requirements, methods and procedures for data systems and databases.


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