Principal Engineer

About UsCoffeeBeans Consulting is a tech consulting firm focused on making organizations AI-ready by structuring their data efficiently across various sources and enabling AI-driven solutions. We specialize in data architecture, pipelines, governance, MLOps, and Gen AI solutions, helping clients achieve faster 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 ResponsibilitiesSolution ArchitectureEngage with clients to understand business goals, technical constraints, and AI / data maturity.Translate requirements into scalable solution blueprints across tech stack and infrastructure.Expert in microservices and design patterns. data, analytics, AI, and cloud .Define end-to-end architecture covering ingestion, storage, processing, analytics, ML / AI, and visualization.Ensure designs meet security, compliance, and governance requirements.Data Architecture & EngineeringArchitect modern data platforms (data lakes, lakehouses, warehouses) using tools like Databricks, Snowflake, BigQuery, Redshift, etc.Design robust ETL / ELT pipelines , streaming architectures, and real-time analytics solutions.Define data models, metadata management, and master data strategies .Implement data governance frameworks (e.g., CDMC, DAMA DMBOK).AI & MLOps EnablementIntegrate ML / Gen AI solutions into the data platform architecture.Work with Data Scientists to operationalize AI models using MLOps best practices.Evaluate LLM integration , vector databases, and AI agents within enterprise architectures.Leadership & DeliveryProvide technical leadership to 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 & Experience12+ years in data engineering, data architecture, or solution architecture roles.Hands-on expertise in cloud platforms (AWS, GCP, Azure) and IaC (Terraform, CloudFormation).Strong knowledge of data modeling , SQL / NoSQL databases , streaming tech (Kafka, Pub / Sub, Kinesis).Proven experience with Databricks, Snowflake, or equivalent modern data stack tools.Knowledge of data governance, security, and compliance frameworks.Familiarity with AI / ML architectures , MLOps tools (MLflow, Kubeflow), and Gen AI frameworks (LangChain, RAG pipelines).Strong communication and client-facing skills.