Senior Data Engineer

Job Description Role Overview: We are looking for a strong, hands-on, highly autonomous Senior Data Engineer to design, build, and operate the Service Layer platform that powers enterprise Quote-to-Cash (QTC), customer lifecycle, and finance integrations across strategic enterprise applications.

You will be instrumental in building and evolving a cloud-native, event-driven integration platform based on AWS, Kafka, Go and Python, leveraging canonical data models, asynchronous messaging, observability, and resilient orchestration patterns.

The platform processes high-volume business-critical events while providing end-to-end visibility, reliability, security, and scalability.

This role requires deep expertise in distributed systems, event-driven architecture, microservices, data engineering, and cloud-native development.

You will contribute to the design and implementation of Service Layer foundation capabilities including messaging, observability, orchestration, data migration, reconciliation, canonical data management, and operational tooling.

Key responsibilities: 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.

Develop scalable Kafka-based event processing solutions with support for retries, idempotency, sequencing, replay, and fault recovery.

Build secure REST APIs through AWS API Gateway and integrate with SaaS platforms / Enterprise Applications.

Build and support 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.

Define and enforce engineering standards, secure-by-design principles, cloud best practices, data governance and non-functional requirements for resilience, scalability, and supportability.

Collaborate with distributed engineering teams and cross-functional stakeholders to translate business requirements into scalable data solutions delivered within agreed timelines.

Participate in architecture reviews, production support, root-cause analysis, performance optimization, and operational readiness activities.

Must Have Skills: Strong hands-on experience in Golang and Python for building scalable backend services, event-driven integrations, orchestration workflows, and data processing solutions.

Strong experience designing and building cloud-native applications on AWS, including AWS Lambda, API Gateway, S3, RDS/Aurora PostgreSQL, DynamoDB, SQS, SNS, EventBridge, IAM, CloudWatch, VPC, and related serverless architecture patterns.

Strong experience designing and operating event-driven and asynchronous systems using Kafka, AWS MSK, RabbitMQ, or equivalent messaging technologies.

Strong understanding of distributed systems architecture, including scalability, resiliency, fault tolerance, idempotency, retry patterns, dead-letter queues, message replay, and eventual consistency.

Strong experience with PostgreSQL, ClickHouse, relational databases, and NoSQL databases such as DynamoDB, including data modelling, query optimization, and performance tuning.

Hands-on experience designing and implementing RESTful APIs, integration services, and enterprise system interfaces using secure API design principles.

Experience building and enforcing canonical data models, data contracts, transformation layers, and validation frameworks for enterprise integrations.

Hands-on experience building and supporting high-availability, business-critical applications on AWS with strong focus on performance, reliability, and operational supportability.

Experience with CI/CD pipelines, automated testing, code quality, and secure software delivery practices, using tools such as GitLab CI, Jenkins, SonarQube, Trivy, Semgrep etc.

Experience with observability, monitoring, and operational analytics, using CloudWatch, Grafana, Datadog, Prometheus, OpenTelemetry, or equivalent platforms.

Strong understanding of cloud security and secure-by-design principles, including IAM, OAuth2, JWT authentication, encryption at rest and in transit, Secrets Manager, vulnerability management, audit logging, and compliance controls.

Strong problem-solving skills with experience in production support, incident management, root cause analysis, and performance optimization within large-scale distributed environments.

Qualifications: Bachelor's degree in Computer Science, Engineering, Information Technology, or related discipline. 7+ years of software engineering experience, with at least 3+ years focused on data engineering and distributed data platforms. 3+ years building cloud-native solutions on AWS. 3+ years of experience working with Golang, Python, AWS Service, and Kafka in production environments.

Experience designing and supporting highly available enterprise integration platforms.

Nice to have: AWS certifications such as AWS Certified Data Engineer – Associate, AWS Certified Solutions Architect – Associate, AWS Certified Developer, or equivalent.

Experience in Quote-to-Cash, CRM, ERP, Customer Lifecycle Management, or Enterprise Data domains.

We're proud to have been recognised as a Great Place to Work® in India ‘25 Career Stage: Senior Associate London Stock Exchange Group (LSEG) Information: Join us and be part of a team that values innovation, quality, and continuous improvement.

If you're ready to take your career to the next level and make a significant impact, we'd love to hear from you.

LSEG is a leading global financial markets infrastructure and data provider.

Our purpose is driving financial stability, empowering economies and enabling custome