(Urgent) Principal Engineer
4 weeks ago
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
- 12+ 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.
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