Role Overview:

We are seeking a Technical Architect who will be responsible for designing, defining, and guiding the overall technical architecture of our projects while maintaining strong hands-on development expertise. The ideal candidate will collaborate across Frontend, Backend, DevOps, and Data Engineering domains to build scalable, efficient, and high-performing solutions that adhere to best practices. You will also act as a technical mentor and thought leader, providing guidance to engineering teams and staying ahead of emerging technologies, including AI/ML and Large Language Model (LLM) ecosystems.

Experience

10+ years (including a minimum of 2 years in a Data Architect role)

Responsibilities:

• Design and architect scalable, high-performance, and secure data platforms (Data Warehouses, Data Lakes, Lakehouse) to support analytics, AI/ML, and reporting needs.
• Leverage Big Data technologies such as PySpark, Hadoop, Kafka, and Databricks for large-scale data processing and transformation.
• Develop and maintain conceptual, logical, and physical data models aligned with business requirements and governance standards.
• Architect data integration pipelines to enable seamless data flow across diverse systems, including legacy and modern cloud platforms (Databricks, Snowflake, AWS, Azure).
• Lead modernization and migration initiatives from on-premises databases (e.g., Informix, Oracle) to cloud-native platforms (AWS, Azure, Google Cloud).
• Continuously optimize data pipelines and storage for performance, scalability, cost efficiency, and SLA adherence.
• Partner with business development teams to provide technical leadership during pre-sales engagements, including client workshops and architecture discussions.
• Collaborate with data engineers, data scientists, business analysts, and IT teams to ensure architecture alignment with business goals.
• Define and enforce data governance frameworks, quality standards, and security policies to ensure compliance with organizational and regulatory requirements.
• Evaluate emerging technologies and tools to define long-term data strategy and ensure future scalability.

Key Skills:

• Backend: Java (Spring Boot, Microservices, REST APIs), Python (Django, Fast API, Flask), Node.js (Express)
  Frontend: React, Angular, with JavaScript/TypeScript skills.
• Data Engineering: ETL/ELT pipelines, data warehousing, streaming architectures (Kafka, Spark).
• Cloud & DevOps: AWS, Azure, GCP, Docker, Kubernetes, CI/CD, Infrastructure-as-Code.
• Databases & Messaging: PostgreSQL, MySQL, MongoDB, Redis, Elasticsearch; event-driven architectures and message queuing.
• Skills: System design, architecture patterns, distributed systems, scalability, performance, and security.
• Leadership: Team mentoring, Agile/Scrum experience, strong communication and collaboration skills