Principal Cloud Data Engineer

This is a fully remote position, open to applicants in Massachusetts.

📋 Description

• Develop comprehensive data solutions from start to finish that facilitate AI insights and applications.

• Convert product specifications into scalable, production-ready data pipelines and products.

• Create ingestion, transformation, and serving layers for enterprise-level AI platforms.

• Design embedding, vector, and retrieval pipelines for RAG workflows, AI agents, and various applications.

• Provide curated datasets and semantic layers for analytics, copilots, and AI-driven decision-making support.

• Architect, construct, and enhance multicloud data solutions with Microsoft Azure as the main platform.

• Implement consistent data engineering methodologies across Azure, Google Cloud, and AWS.

• Utilize the Microsoft Fabric ecosystem and Snowflake to integrate data engineering and analytics operations.

• Design, create, and sustain scalable ELT/ETL pipelines sourced from APIs, databases, files, SaaS applications, and streaming data.

• Implement lakehouse and medallion architectures; optimize computing, storage, and access control mechanisms.

• Leverage Informatica and Fabric IQ for managing data catalogs, lineage tracking, quality assurance, profiling, cleansing, validation, and application integration.

• Provide guidance on Semarchy master data management solutions.

• Enforce access controls, data classification, and compliance measures.

• Establish automated testing, monitoring, and observability for pipeline health, freshness, quality, and cost efficiency.

• Collaborate with Enterprise Architecture, product engineering, business, and operations teams to outline the AI data roadmap.

• Develop reusable data engineering patterns, frameworks, and standards.

• Mentor engineers in multicloud and AI-enablement methodologies.

• Assess emerging tools and technologies.

• Deliver scalable, reliable, governed, and AI-ready data products.

⛳️ Requirements

• 8–10 years of professional experience in data engineering.

• The most recent 2–3 years should focus on contemporary cloud data engineering initiatives supporting AI products and analytics.

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related discipline.

• Strong expertise in SQL and Python for data engineering and pipeline construction.

• Experience in multicloud data engineering, primarily with Microsoft Azure.

• Robust hands-on experience with the Microsoft Fabric ecosystem.

• Proven track record in engineering AI-enabling data solutions, including RAG/embedding pipelines and semantic layers.

• Familiarity with integrating Azure AI Foundry, Google Vertex AI, and Snowflake Cortex AI.

• Strong knowledge of AI tools such as Anthropic Claude or the Microsoft Copilot suite.

• Practical experience with data governance, quality assurance, and application integration using tools like Informatica.

• Familiarity with Semarchy or similar master data management platforms.

• Experience with lakehouse/medallion and dimensional data modeling techniques.

• Knowledge of CI/CD methodologies for data utilizing Azure DevOps or GitHub Actions.

• Experience with testing and observability practices.

• Proven capability to mentor and enhance team skills.

• Strong collaborative and communication abilities across technical, product, and business units.

• Analytical mindset focused on achieving measurable business and AI results.

🏝️ Benefits

• Discretionary bonuses based on financial performance.

• Medical insurance coverage.

• Dental insurance coverage.

• Vision insurance coverage.

• Flexible Spending Accounts.

• Retirement savings plans.

• Life insurance coverage.

• Disability insurance coverage.

• Paid vacation time.

• Paid holidays.

• Tuition assistance programs.