Data Platform Engineer/Analyst

The Data Platform Engineer/Analyst role is part of the Data Platform team, focusing on designing and building streaming and data-store solutions using technologies such as Apache Kafka, Kafka Connect, Spring Boot, MongoDB, GraphQL, and Apache Iceberg.

• Minimum 3 years of production experience with strong knowledge of Kafka brokers, topics, partitioning, schemas, and replication.
• Proficiency with Kafka Streams and kSQL.
• Experience configuring and developing Kafka Connect connectors (off-the-shelf and custom).
• Strong proficiency in Java and the Spring ecosystem (Spring Boot, Cloud, Security, Data).
• Proficiency in Java and Python for integrations and tooling.
• Experience designing document-oriented schemas, indexing, and query optimization in MongoDB.
• Experience implementing GraphQL services including schema design and resolver development.
• Familiarity with Apache Iceberg table formats and metadata management.
• Experience with Prometheus, Grafana, and OpenTelemetry for monitoring.
• Knowledge of TLS, SASL, ACLs, and encryption of data at rest and in transit.
• Experience working in Scrum/Kanban teams and using Jira and Confluence.

• Collaborate with business analysts and IT teams to understand business processes and data flows.
• Create and maintain functional and technical documentation such as use cases, user stories, data diagrams, and field mappings.
• Design Kafka topics with naming conventions, partition strategies, and Avro schemas.
• Define data structures for MongoDB collections, GraphQL models, and Apache Iceberg tables.
• Develop Spring Boot microservices for producers, consumers, and stream processing.
• Implement the GraphQL layer (schemas and resolvers) to expose data stored in MongoDB.
• Configure and extend Kafka Connect connectors, including building custom connectors.
• Develop custom Single Message Transforms (SMTs) and data format converters.
• Implement monitoring, logging, and observability using Prometheus, Grafana, Vector/ELK, OpenTelemetry, and Dynatrace.
• Diagnose and resolve issues related to replication, latency, and data inconsistencies.
• Optimize Kafka, MongoDB, and Iceberg configurations for performance and cost efficiency.
• Work in an Agile environment (Scrum or Kanban) alongside Data Engineers, DevOps, Analysts, and QA Engineers.
• Share knowledge through workshops, documentation, and code reviews.