Senior / Lead Data Engineer – Service Layer / QTC Integration Platform
Senior/Lead Data Engineer to design, build, and operate a Quote-to-Cash (QTC) Service Layer integration platform in Bengaluru (hybrid): building event-driven microservices in Go and Python on AWS (Lambda, Kafka/MSK), ETL/migration/reconciliation pipelines with Snowflake, PostgreSQL, and ClickHouse, plus mentoring a team. 12-month contract at ~27 LPA.
Compensation
₹2.7M / yr
Location
Bengaluru, India
Work setup
Not specified
Seniority
Lead
Employment
Contract
Experience
4+ years
Category
Data engineering
Posted
Skills
api
api-design
api-gateway
aurora
authentication
aws
aws-glue
ci-cd
clickhouse
cloud
cloud-native
cloud-security
cloudwatch
crm
data-engineering
data-governance
data-modeling
data-quality
datadog
devops
distributed-systems
dynamodb
erp
etl
event-driven-architecture
eventbridge
gitlab
go
grafana
iam
jenkins
jwt
kafka
lambda
microservices
nosql
oauth
observability
opentelemetry
postgresql
prometheus
python
rabbitmq
rdbms
rds
rest
root-cause-analysis
s3
serverless
snowflake
sns
solution-design
sonarqube
sqs
stakeholder-management
test-automation
vpc
vulnerability-management
Must have
8+ years of software engineering experience
4+ years focused on cloud-native, data engineering, integration, or distributed platforms
4+ years building cloud-native solutions on AWS
4+ years working with Go/Golang, Python, AWS services, and Kafka in production
Strong hands-on experience in Go/Golang and Python
Proven experience leading and mentoring engineering teams (task planning, code reviews, delivery management)
Domain Exposure: Quote-to-Cash, CRM, ERP, Customer Lifecycle, Enterprise Data preferred
Experience: 8+ years
Location/ Mode: Bengaluru/Hybrid
Budget: 27 LPA
Contract Duration: 12 months
Role Overview
We are looking for a strong, hands-on, and highly autonomous Senior / Lead Data Engineer to design, build, and operate the Service Layer platform powering enterprise Quote-to-Cash (QTC), customer lifecycle, finance, and enterprise application integrations.
This role requires deep expertise in distributed systems, event-driven architecture, microservices, data engineering, cloud-native development, and platform reliability. The candidate will also provide technical leadership to a team of engineers, driving solution design, engineering standards, delivery execution, and operational support across multiple integration initiatives.
The platform is built using AWS, Kafka / AWS MSK, Go, Python, canonical data models, asynchronous messaging, and cloud-native architecture patterns, processing high-volume, business-critical events with strong focus on reliability, security, scalability, observability, and operational readiness.
Key Responsibilities
Technical Delivery & Engineering Leadership
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 through task planning, technical guidance, code reviews, design reviews, and delivery management.
Drive engineering best practices across software development, CI/CD, observability, resiliency, security, and cloud-native architecture.
Manage multiple concurrent initiatives while balancing business priorities, technical debt, and platform evolution.
Architecture & Platform Design
Drive architecture and design decisions for event-driven integrations, canonical data models, orchestration frameworks, and platform capabilities.
Senior / Lead Data Engineer – Service Layer / QTC Integration Platform at TALPRO INDIA PRIVATE LIMITED (Bengaluru, India) — aijobsearch
Proven experience designing, building, and operating highly available enterprise integration and event-driven platforms
Strong experience in production support, incident management, root-cause analysis, and performance optimization
Experience with observability/monitoring tools (CloudWatch, Grafana, Datadog, Prometheus, OpenTelemetry)
Bachelor's degree in Computer Science, Engineering, IT, or related discipline
Define and enforce engineering standards, secure-by-design principles, cloud best practices, data governance, and non-functional requirements.
Design and build scalable Service Layer foundation capabilities including messaging, orchestration, observability, reconciliation, data migration, operational tooling, and canonical data management.