JOB  DETAILS

Responsibilities:

• Design and implement robust, scalable components for ingesting, processing, and persisting high-frequency telemetry data.
• Collaborate with data scientists to host, orchestrate and optimize workloads in Python, Scala, and Java.
• Design and build components using technologies like Apache Spark, Delta Lake, Redis/Valkey, MQTT, and PostgreSQL.
• Drive modernization efforts including:
  • Containerization and deployment on Kubernetes
  • Integration with S3-compatible object stores (e.g., Ceph)
• Evaluate and integrate emerging technologies (e.g., Flink, Trino, Kafka, DuckDB, Dask, Daft) to optimize performance and scalability.
• Use your experience to contribute to architectural decisions involving event sourcing, CQRS, and hybrid cloud deployments.

Ideal Candidate Profile

• Extensive experience in backend development with languages such as Java, Scala and Python.
• Proven track record working in teams to develop large, complex applications.
• Deep understanding of streaming and batch data processing, ideally with Apache Spark or similar.
• Experience with containerization (Docker) and orchestration (Kubernetes).
• Familiarity with data lake/lakehouse architectures, especially Delta Lake.
• Strong knowledge of message brokers (MQTT, Kafka) and caching systems (Redis/Valkey).
• Comfortable working across multiple languages (Java, Python, Scala).
• Experience in designing systems for scalability, multi-tenancy, and hybrid deployments.
• Prior experience in Data Engineering roles, and expertise in machine learning algorithms and statistical modelling will be highly regarded
• Mining Industry knowledge will be desirable, however not mandatory

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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