Principal Cloud Data Engineer
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Job Description
Cloud data engineer building governed, AI-ready data pipelines for Teradyne’s global test and automation solutions. Enabling enterprise AI, analytics, and operational insights across multicloud platforms.
Responsibilities:
- Engineer end-to-end data solutions that drive AI insights and implementations
- Translate product requirements into scalable, production-grade data pipelines and data products
- Build ingestion, transformation, and serving layers for enterprise AI platforms
- Develop embedding, vector, and retrieval pipelines for RAG workflows, AI agents, and applications
- Deliver curated datasets and semantic layers for analytics, copilots, and AI-driven decision support
- Design, build, and optimize multicloud data solutions with Microsoft Azure as the primary platform
- Apply consistent data engineering patterns across Azure, Google Cloud, and AWS
- Use the Microsoft Fabric ecosystem and Snowflake to unify data engineering and analytics workloads
- Design, develop, and maintain scalable ELT/ETL pipelines from APIs, databases, files, SaaS applications, and streaming sources
- Implement lakehouse and medallion architectures; tune compute, storage, and access controls
- Leverage Informatica and Fabric IQ for data catalogs, lineage, quality, profiling, cleansing, validation, and application integration
- Advise on Semarchy master data management solutions
- Apply access controls, data classification, and compliance safeguards
- Build automated testing, monitoring, and observability for pipeline health, freshness, quality, and cost
- Partner with Enterprise Architecture, product engineering, business, and operations teams on the AI data roadmap
- Establish reusable data engineering patterns, frameworks, and standards
- Mentor engineers on multicloud and AI-enablement practices
- Evaluate emerging tools and technologies
- Deliver scalable, trusted, governed, and AI-ready data products
Requirements:
- 8–10 years of experience in data engineering
- Last 2–3 years focused on modern cloud data engineering projects enabling AI products and analytics
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field
- Strong proficiency in SQL and Python for data engineering and pipeline development
- Multicloud data engineering experience with Microsoft Azure as primary
- Strong, hands-on experience with the Microsoft Fabric ecosystem
- Experience engineering AI-enabling data solutions, including RAG/embedding pipelines and semantic layers
- Experience integrating with Azure AI Foundry, Google Vertex AI, and Snowflake Cortex AI
- Strong proficiency in AI tooling such as Anthropic Claude or Microsoft Copilot suite
- Hands-on experience with data governance, data quality, and application integration using tools such as Informatica
- Experience with Semarchy or comparable master data management tools
- Experience with lakehouse/medallion and dimensional data modeling
- Experience with CI/CD for data using Azure DevOps or GitHub Actions
- Experience with testing and observability
- Proven ability to mentor and upskill teams
- Strong collaboration and communication skills across technical, product, and business teams
- Analytical mindset focused on measurable business and AI outcomes
Benefits:
- Discretionary bonus(es) based on financial performance
- Medical insurance
- Dental insurance
- Vision insurance
- Flexible Spending Accounts
- Retirement savings plans
- Life insurance
- Disability insurance
- Paid vacation
- Paid holidays
- Tuition assistance programs
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