Coffeebeans.io - Solutions Architect - Data Engineering

About Us CoffeeBeans 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 Responsibilities - Solution Architecture: - Engage 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 & Engineering: - Architect 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 Enablement: - Integrate 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 & Delivery: - Provide 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 & Experience - 10+ 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. (ref:hirist.tech)