Principal Engineer

4 days ago

New Delhi, India CoffeeBeans Full time

About Us CoffeeBeans Consulting is a tech consulting firm focused on making organizationsAI-readyby structuring their data efficiently across various sources and enabling AI-driven solutions. We specialize indata architecture, pipelines, governance, MLOps, and Gen AIsolutions, helping clients achievefaster go-to-market and cost efficiency . We are looking for a Principal Engineer who can design and implement complex solutions that are scalable, future-proof and AI led.Key Responsibilities Solution Architecture Engage with clients to understand business goals, technical constraints, and AI/data maturity. Translate requirements intoscalable solution blueprintsacross tech stack and infrastructure. Expert in microservices and design patterns.data, analytics, AI, and cloud . Defineend-to-end architecturecovering ingestion, storage, processing, analytics, ML/AI, and visualization. Ensure designs meetsecurity, compliance, and governancerequirements. Data Architecture & Engineering Architectmodern data platforms(data lakes, lakehouses, warehouses) using tools like Databricks, Snowflake, BigQuery, Redshift, etc. Design robustETL/ELT pipelines , streaming architectures, andreal-time analyticssolutions. Definedata models, metadata management, and master data strategies . Implementdata governance frameworks(e.g., CDMC, DAMA DMBOK). AI & MLOps Enablement IntegrateML/Gen AI solutionsinto the data platform architecture. Work with Data Scientists tooperationalize AI modelsusing MLOps best practices. EvaluateLLM integration , vector databases, and AI agents within enterprise architectures. Leadership & Delivery Providetechnical leadershipto engineering teams. Review designs, code, and deployment plans for quality and scalability. Work closely with client stakeholders, delivery managers, and CTO to ensure success. Required Skills & Experience 12+ yearsin data engineering, data architecture, or solution architecture roles. Hands-on expertise incloud platforms(AWS, GCP, Azure) andIaC(Terraform, CloudFormation). Strong knowledge ofdata modeling ,SQL/NoSQL databases ,streaming tech(Kafka, Pub/Sub, Kinesis). Proven experience withDatabricks, Snowflake, or equivalentmodern data stack tools. Knowledge ofdata governance, security, and complianceframeworks. Familiarity withAI/ML architectures , MLOps tools (MLflow, Kubeflow), and Gen AI frameworks (LangChain, RAG pipelines). Strong communication and client-facing skills.

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