Description
We are looking for a strong, hands-on, highly autonomous Senior Data Engineer to design, build, and operate our enterprise People Function Capability Layer.
You will be instrumental in delivering a secure, reliable, scalable, and cost-efficient service layer that integrates multiple systems across the People ecosystem.
Key Responsibilities:
- Build and lead the development of high-performance, event-driven integration pipelines, applying strong debugging and performance optimization skills to ensure resilient data flows.
- Define and enforce technical standards, design patterns, and engineering best practices across development, security and data governance.
- Design and enforce canonical data models and schemas to standardize complex organizational data domains across systems.
- Build and manage CI/CD pipelines to enable reliable, repeatable, and automated software delivery.
- Drive observability and monitoring using tools such as Datadog and Grafana to ensure system reliability and performance.
- Collaborate with distributed engineering teams and cross-functional stakeholders to translate business requirements into scalable data solutions delivered within agreed timelines.
- Design, provision, and manage AWS infrastructure to ensure high availability, scalability, and low-latency processing for data workloads.
Must Have Skills:
- Strong hands-on experience in Golang and Python for backend and data engineering use cases.
- Strong hands-on experience with AWS cloud services – AWS Lambda, SQS, SNS, EC2, S3, RDS, API Gateway, VPC, EKS, ECS, IAM, CloudWatch and cloud-native architecture patterns.
- Strong experience with relational databases (e.g., PostgreSQL, MS SQL) and NoSQL stores (e.g., DynamoDB).
- Strong hands-on experience with message brokers and event-driven architectures (e.g., Kafka, RabbitMQ).
- Hands-on experience designing and implementing RESTful APIs and data services.
- Hands-on experience with CI/CD tools (e.g., Jenkins, GitLab CI).
- Experience building highly available, distributed systems on AWS, including containerization using Docker.
- Hands on experience building highly available distributed systems in AWS and containerization using Docker.
- Experience with observability platforms such as Datadog, Prometheus, or equivalent.
- Strong understanding of cloud security best practices including IAM, encryption, secrets management, vulnerability scanning, and compliance controls.
Qualifications:
- Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience.
- 5+ years of software engineering experience, with at least 3+ years focused on data engineering or distributed data platforms.
- 3+ years of experience working with Golang, Python, AWS, and Kafka in production environments.
Nice to have:
- AWS certifications such as AWS Certified Data Engineer – Associate, AWS Certified Solutions Architect – Associate, AWS Certified Developer – Associate.
Benefits:
- LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.