Key Responsibilities

1. Architectural Strategy Design

- - Design and implement resilient, event-driven microservices architectures utilizing .NET Core and Java/Spring Boot.
- Architect and scale modern data solutions (ETL/ELT pipelines, data lakes, and data warehouses) across multiple major cloud platforms like Databricks, Snowflake, BigQuery, or Microsoft Fabric.
- Define standard patterns for integrating operational application layers with analytical data systems seamlessly.

2. Hands-on Execution Engineering Excellence

- - Maintain a hybrid approach by remaining hands-on with architecture blueprints, system design, prototyping, and high-impact code reviews.
- Lead by example to champion clean code, robust CI/CD pipelines, containerization (Kubernetes/Docker), and reliable distributed systems.
- Troubleshoot complex architectural bottlenecks across application and data layers.

3. AI Intelligent Automation

- - Drive the production deployment of Agentic AI frameworks, autonomous workflows, and sophisticated prompt engineering protocols.
- Architect robust Retrieval-Augmented Generation (RAG) pipelines that bridge enterprise application microservices with large-scale analytical data stores safely and securely.

4. Technical Leadership Calibration

- - Mentor, guide, and upskill senior engineers, tech leads, and software architects.
- Collaborate closely with Practice Owners and Business Leaders to align engineering capabilities with client demands and emerging technology trends.

Technical Requirements Qualifications

Core Experience





- - 12 15+ years of progressive experience in software engineering and enterprise architecture.
- Proven track record of operating at a Director, Principal Architect, or Chief Architect level, managing complex multi-system environments.

Application Engineering Frameworks

- - Advanced, deep-dive expertise in .NET Core and/or Java/Spring Boot.
- Extensive hands-on experience with Microservices architectures, domain-driven design (DDD), and distributed systems.
- Deep knowledge of Event-Driven Frameworks and messaging infrastructure (e.g., Kafka, RabbitMQ, AWS Kinesis).

Enterprise Data Ecosystems

- - Deep, practical knowledge of Enterprise Data Architecture, data modeling, and robust ETL/ELT engineering.
- Production-grade, hands-on experience in at least 2 to 3 of the following modern platforms:
- Databricks (Delta Lake, Unity Catalog, Spark)
- Snowflake (Snowpark, Streamlit, Data Sharing)
- Google BigQuery
- Microsoft Fabric

Generative AI Automation

- - Foundational or production experience deploying Agentic AI systems (e.g., LangChain, AutoGen, CrewAI, or semantic kernels).
- Solid capability in structured prompt engineering, vector database implementation (e.g., Pinecone, Milvus, pgvector), and securing LLM-orchestrated applications.

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Data Architect (Hyderabad)
🏢 Paltech
📍 Hyderabad