Cloud Data Engineering

Technical Lead (Hybrid Cloud, Data & Software Engineering)

Experience: 8+ Years

Work Location: Bangalore, Hyderabad, Pune, Chennai, Noida (Hybrid)

Skill: On-premises ↔ cloud, Data Lake, DataHub, Amundsen

Job Summary

We are looking for an experienced Technical Lead with strong expertise in Hybrid Cloud Architecture, Data Engineering, and Software Engineering. The ideal candidate will be responsible for designing, implementing, and leading enterprise-scale technology solutions across on-premises and cloud environments.

The candidate should have hands-on experience in cloud migration, Kubernetes orchestration, networking, data platforms, event-driven architectures, and modern data engineering tools. The role requires strong technical leadership, architecture design capabilities, and the ability to drive complex technology initiatives.

Experience & Qualifications

• 8+ years of overall IT experience in Software Engineering, Data Engineering, Cloud, or Infrastructure Engineering.
• Proven experience in a Technical Lead or equivalent senior engineering role.
• Strong hands-on technical and architectural expertise.
• Experience leading technical teams and delivering enterprise-scale solutions.
• Excellent problem-solving, communication, and stakeholder management skills.
• Ability to work independently and collaboratively in a hybrid work environment.

Key Responsibilities

• Lead the design, development, and implementation of hybrid cloud architecture solutions.
• Drive migration strategies and execution between on-premises infrastructure and cloud environments.
• Design and manage scalable Kubernetes-based platforms using Rancher and Azure Kubernetes Service (AKS).
• Define and implement enterprise networking solutions involving VXLAN, MPLS, and secure connectivity.
• Implement Zero Trust security principles across hybrid infrastructure.
• Architect and manage enterprise Data Lakes and Data Warehouses.
• Design data storage and processing solutions using Delta Lake, Parquet, and Cloud Object Storage.
• Lead the implementation of metadata management and data catalog solutions using DataHub and Amundsen.
• Drive ETL/ELT pipeline development using dbt, Apache Spark, and Python.
• Design and implement event-driven architectures using Apache Kafka and EventStore.
• Provide technical guidance and mentorship to engineering teams.
• Collaborate with architects, product owners, DevOps, infrastructure, and security teams to deliver scalable solutions.
• Establish technical standards, best practices, and engineering guidelines.

Required Technical Skills

1. Hybrid Cloud Architecture & Infrastructure

• Strong experience in designing and implementing hybrid cloud architectures.
• Hands-on experience with on-premises to cloud and cloud to on-premises migration.
• Kubernetes orchestration experience with Rancher and AKS.
• Strong understanding of containerization and orchestration using Docker and Kubernetes.

2. Networking & Security

• Knowledge of enterprise networking concepts, including VXLAN and MPLS.
• Understanding of network architecture, connectivity, and troubleshooting.
• Experience implementing Zero Trust security principles.
• Understanding of cloud and infrastructure security best practices.

3. Data Engineering & Data Architecture

• Experience designing and implementing Data Lakes and Data Warehouses.
• Strong knowledge of Delta Lake and Parquet data formats.
• Experience with metadata catalog and data discovery platforms such as DataHub and Amundsen.
• Hands-on experience with ETL/ELT frameworks such as dbt and Apache Spark.
• Strong Python programming and data processing skills.

4. Event-Driven Architecture & Integration

• Experience designing event-driven architectures using Apache Kafka.
• Understanding of Lake and EventStore architecture patterns.
• Experience with Cloud Object Storage and event streaming platforms.
• Knowledge of API management and integration using Apigee.
• Familiarity with Model Context Protocol (MCP) and its ecosystem.

5. DevOps & Software Engineering

• Strong software engineering fundamentals and solution design capabilities.
• Experience with Docker, Kubernetes, and container-based application deployment.
• Understanding of CI/CD, automation, and modern DevOps practices.
• Ability to drive technical design discussions and architecture decisions.

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