Snowflake Data Engineer with AWS

Tata Consultancy Services; Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Tata Consultancy Services in Bengaluru seeks a senior engineering leader to own end-to-end technical delivery of key initiatives. You will lead and mentor a team of engineers, driving architecture decisions for event-driven integrations and platform capabilities.

The role requires enforcing secure-by-design principles, cloud best practices, and data governance while delivering scalable, observable, and resilient systems across enterprise applications.

Responsibilities

• Own end-to-end technical delivery of key initiatives, ensuring solutions are delivered with quality, scalability, security, and operational readiness.
• Lead and mentor a team of engineers, fostering technical excellence, knowledge sharing, and continuous improvement across the team.
• Drive architecture and design decisions for event-driven integrations, canonical data models, orchestration frameworks, and platform capabilities.
• Define and enforce engineering standards, secure-by-design principles, cloud best practices, data governance and non-functional requirements for resilience, scalability, and supportability.
• Design, develop, and operate real-time event-driven integration services using Golang and Python.
• Build and enhance the Service Layer platform that orchestrates Quote-to-Cash workflows across enterprise applications.
• Design and implement canonical data models, transformation frameworks, validation rules, and integration contracts that standardize communication across multiple business systems.
• Design and implement scalable Kafka-based event processing solutions with support for retries, idempotency, sequencing, replay, and fault recovery.
• Design and implement large-scale ETL, migration, reconciliation, and data-quality solutions using AWS Glue, Step Functions, Snowflake, PostgreSQL, and ClickHouse.
• Design and implement observability, monitoring, alerting, and operational dashboards to enable end-to-end workflow visibility and supportability.
• Partner with Product Managers, Architects, Enterprise Data teams, and other cross-functional stakeholders to define technical roadmaps and execution plans.
• Lead code reviews, design reviews, technical governance activities, and engineering best-practice adoption across the team.
• Drive engineering standards covering software development lifecycle, CI/CD, security, observability, resiliency, and cloud-native architecture patterns.

Job description

• Own end-to-end technical delivery of key initiatives, ensuring solutions are delivered with quality, scalability, security, and operational readiness.
• Lead and mentor a team of engineers, fostering technical excellence, knowledge sharing, and continuous improvement across the team.
• Drive architecture and design decisions for event-driven integrations, canonical data models, orchestration frameworks, and platform capabilities.
• Define and enforce engineering standards, secure-by-design principles, cloud best practices, data governance and non-functional requirements for resilience, scalability, and supportability.
• Design, develop, and operate real-time event-driven integration services using Golang and Python.
• Build and enhance the Service Layer platform that orchestrates Quote-to-Cash workflows across enterprise applications.
• Design and implement canonical data models, transformation frameworks, validation rules, and integration contracts that standardize communication across multiple business systems.
• Design and implement scalable Kafka-based event processing solutions with support for retries, idempotency, sequencing, replay, and fault recovery.
• Design and implement large-scale ETL, migration, reconciliation, and data-quality solutions using AWS Glue, Step Functions, Snowflake, PostgreSQL, and ClickHouse.
• Design and implement observability, monitoring, alerting, and operational dashboards to enable end-to-end workflow visibility and supportability.
• Partner with Product Managers, Architects, Enterprise Data teams, and other cross-functional stakeholders to define technical roadmaps and execution plans.
• Lead code reviews, design reviews, technical governance activities, and engineering best-practice adoption across the team.
• Drive engineering standards covering software development lifecycle, CI/CD, security, observability, resiliency, and cloud-native architecture patterns.