Role Overview
We are looking for a hands-on Senior / Lead Data Engineer to design, develop, and manage a cloud-native integration platform supporting Quote-to-Cash (QTC), customer lifecycle, finance, and enterprise application integrations.
The ideal candidate should have strong expertise in Go/Golang, Python, AWS, Kafka/MSK, microservices, distributed systems, and data engineering, along with the ability to lead engineering teams and manage end-to-end technical delivery.
Key Responsibilities
- Design, develop, and maintain event-driven integration services using Go/Golang and Python.
- Lead technical delivery, mentor engineers, conduct code reviews, and manage project execution.
- Design scalable architectures for microservices, distributed systems, and enterprise integrations.
- Develop and manage Kafka/AWS MSK-based event processing and asynchronous workflows.
- Build REST APIs and integration services for enterprise applications.
- Design and implement ETL, data migration, reconciliation, and data quality solutions.
- Work with AWS Glue, Step Functions, Snowflake, PostgreSQL, and ClickHouse.
- Develop cloud-native applications using AWS services.
- Implement CI/CD pipelines, secure coding practices, and automated testing.
- Monitor platform performance, troubleshoot production issues, and perform root cause analysis.
- Collaborate with product, architecture, engineering, DevOps, and business teams to ensure successful delivery.
Required Technical Skills
Programming & Backend Development
- Strong hands-on experience with Go/Golang and Python.
- REST API development and secure API design.
- Backend services, data processing, and orchestration workflows.
AWS & Cloud-Native Technologies
- AWS Lambda, API Gateway, S3, RDS/Aurora PostgreSQL, DynamoDB, SQS, SNS, EventBridge, IAM, CloudWatch, and VPC.
- Strong understanding of AWS serverless architecture.
Kafka & Distributed Systems
- Kafka/AWS MSK and event-driven architecture.
- Microservices and distributed systems.
- Asynchronous messaging, retries, idempotency, message replay, fault recovery, and dead-letter queues.
Data Engineering & Databases
- PostgreSQL, ClickHouse, DynamoDB, and relational/NoSQL databases.
- Data modelling, query optimization, performance tuning, and data validation.
- AWS Glue, Step Functions, Snowflake, ETL, and data reconciliation.
DevOps, Security & Monitoring
- CI/CD tools such as GitLab CI and Jenkins.
- Security tools such as SonarQube, Trivy, and Semgrep.
- IAM, OAuth2, JWT, encryption, Secrets Manager, and vulnerability management.
- Monitoring tools such as CloudWatch, Grafana, Datadog, Prometheus, and OpenTelemetry.
Eligibility Criteria
- Bachelor's degree in Computer Science, Engineering, Information Technology, or a related discipline.
- Minimum 8+ years of software engineering experience.
- At least 4+ years of experience in cloud-native development, data engineering, integration, or distributed platforms.
- At least 4+ years of hands-on experience with AWS, Go/Golang, Python, and Kafka in production environments.
- Proven experience leading and mentoring engineering teams.
- Experience with architecture design, technical delivery, production support, incident management, and performance optimization.
Good to Have
- AWS certifications such as AWS Certified Data Engineer – Associate, AWS Certified Solutions Architect – Associate, or AWS Certified Developer – Associate.
- Experience in Quote-to-Cash (QTC), CRM, ERP, customer lifecycle management, or enterprise data.
- Exposure to finance, billing, and large-scale enterprise integration projects.
Pay: ₹2,500,000.00 - ₹2,700,000.00 per year
Work Location: Hybrid remote in Bengaluru, Karnataka
