Project – the aim you’ll have
The project focuses on transitioning from on-prem data warehouse to a modern cloud-based microservices for a major telecommunications provider.
A key component of the initiative is the modernization and adaptation of an existing data flows to the new architecture. The work involves redesigning data flows and funnels, integrating customer data logic with the new data lake ecosystem, and ensuring scalable, real-time access to customer segmentation and analytics.
Position – how you’ll contribute
Your role will focus on building a pure backend environment (no frontend work) within a distributed, microservices-based architecture:
- Configuring and optimizing Apache NiFi to support current business data flows, ensuring scalability and performance of the solution
- Configuring and maintaining ETL processes between legacy systems and AWS (primarily using Apache NiFi)
- Analyzing, designing, and implementing data flows and data processing pipelines
- Data modeling for analytical and operational use cases
- Processing and integrating data from queueing/streaming systems (Kafka)
- Developing ETL pipelines using AWS Glue, Azure Data Factory, or similar tools
- Designing, developing, testing, and deploying backend services in Python
- Building and maintaining microservices-based systems (nice to have)
- Improving and optimizing existing backend and data processing services
- Translating business requirements into robust and scalable technical solutions
- Collaborating with architects, DevOps engineers, and data engineering teams
- Supporting infrastructure and platform integration initiatives
- Working with containerized environments (Docker) and Kubernetes
- Supporting integration with OpenSearch