About this role
As a Data Platform Engineer, you will be a key contributor in building and maintaining the new Operational Data Store. You will develop the infrastructure that captures, stores, and publishes master data across the enterprise, transitioning away from legacy point-to-point integrations to a highly decoupled event-driven architecture.
Key Responsibilities:
- Build and maintain batch and real-time data pipelines using Dataflow and Kafka.
- Design and implement orchestration workflows to manage data processing tasks.
- Collaborate with cross-functional teams to gather requirements and ensure data solutions meet business needs.
- Monitor and optimize data pipeline performance for efficiency and reliability.
- Develop and maintain documentation for data processes and architecture.
Required Skills & Qualifications:
- Strong experience in data engineering principles and practices.
- Proficiency in Dataflow, Kafka, and other data processing tools.
- Familiarity with cloud platforms such as AWS or Azure.
- Experience with SQL and NoSQL databases.
- Knowledge of event-driven architecture and microservices.
- Excellent problem-solving skills and attention to detail.
Experience:
- Minimum of 5-8 years in data engineering or related fields.
What we offer:
- Opportunity to work on innovative projects in a dynamic environment.
- Collaborative team culture with a focus on professional growth.
- Access to the latest tools and technologies in data engineering.
Applications are read by our talent team, usually within two working days.
If you look like a fit we will call you, and you will hear from us either way.