Coffeebeans.io - Solutions Architect - Data Engineering

CoffeeBeans; Bengaluru; On-site; INR 4,000,000 - 5,600,000; Full time

Job summary

CoffeeBeans Consulting is a tech consulting firm focused on making organizations AI-ready by structuring their data efficiently across sources and enabling AI-driven solutions. We are seeking a senior data architecture expert to lead end-to-end data platform design for enterprise clients, covering ingestion, storage, processing, analytics, ML/AI, and governance.

The role requires 10+ years in data engineering or architecture, with hands-on cloud, Databricks/Snowflake, and MLOps experience.

Qualifications

• 10+ years in data engineering, data architecture, or solution architecture roles.
• Hands-on cloud platforms and IaC with security and governance focus.
• Experience architecting data lakes, lakehouses, warehouses and real-time analytics.

Responsibilities

• Engage with clients to understand goals and AI maturity.
• Translate requirements into scalable blueprints across tech stack.
• Define end-to-end architecture for ingestion, storage, processing, analytics, ML/AI, and visualization.
• Architect modern data platforms using Databricks, Snowflake, BigQuery, Redshift.
• Design robust ETL/ELT pipelines and streaming architectures.
• Lead data governance and metadata management initiatives.
• Provide technical leadership to engineering teams and stakeholders.

Skills

Cloud platforms

IaC

Data modeling

Streaming tech

Databricks/Snowflake

MLOps & GenAI

Tools

Terraform

CloudFormation

Databricks

Snowflake

BigQuery

Kafka

Pub/Sub

Kinesis

Job description

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.

Key Responsibilities

• Engage with clients to understand business goals, technical constraints, and AI/data maturity.
• Translate requirements into scalable solution blueprints across tech stack and infrastructure, ensuring designs meet security, compliance, and governance requirements.
• Define end‑to‑end architecture covering ingestion, storage, processing, analytics, ML/AI, and visualization.
• Architect modern data platforms (data lakes, lakehouses, warehouses) using tools such as Databricks, Snowflake, BigQuery, Redshift.
• 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).
• Integrate ML/Gen AI solutions into the data platform architecture and operationalize AI models using MLOps best practices.
• Evaluate LLM integration, vector databases, and AI agents within enterprise architectures.
• Provide technical leadership to engineering teams, reviewing 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 experience with cloud platforms (AWS, GCP, Azure) and IaC (Terraform, CloudFormation).
• Strong knowledge of data modeling, SQL/NoSQL databases, streaming technologies (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.