Solutions Architect Microservices and Data

CoffeeBeans; Bengaluru Urban; On-site; INR 2,000,000 - 3,500,000; Full time

Job summary

A tech consulting firm is seeking a Principal Engineer to design and implement scalable, AI-led solutions. The ideal candidate will have over 12 years of experience in data engineering and architecture. Responsibilities include engaging with clients, architecting modern data platforms, and leading teams. This full-time position requires expertise in cloud platforms like AWS and GCP, with a strong focus on data governance and MLOps. Excellent communication skills are essential.

Qualifications

• 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 and SQL/NoSQL databases.

Responsibilities

• Engage with clients to understand business goals and AI/data maturity.
• Translate requirements into scalable solution blueprints.
• Architect modern data platforms using tools like Databricks and Snowflake.

Skills

Data engineering

Data architecture

Solution architecture

Cloud platforms (AWS, GCP, Azure)

Infrastructure as Code (Terraform, CloudFormation)

Data modeling

SQL/NoSQL databases

Streaming technologies (Kafka, Pub/Sub, Kinesis)

Data governance

MLOps tools (MLflow, Kubeflow)

AI/ML architectures

Strong communication skills

Tools

Databricks

Snowflake

BigQuery

Redshift

Job description

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

• 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.

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.

Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Information Technology

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