Job Description

Mandatory Requirements

. 5-8 years of data engineering experience, including building and deploying large-scale data systems

. Strong hands-on experience designing batch and streaming pipelines using Apache Spark, Apache Flink and Apache Kafka

. Proficiency in Java or Scala for distributed data processing, together with SQL

. Experience deploying and scaling data workloads in containerised Kubernetes environments

. Experience with S3-compatible object storage, data-quality controls, schema and lineage management, checkpointing and recovery, GitLab and CI/CD practices

Preferred Requirements

. Experience working within the SAFe framework

. Experience developing data solutions for safety-critical and mission-critical systems

. Experience with MinIO or equivalent S3-compatible object storage schema and lineage design data-quality checks metadata preservation bronze/silver/gold layered processing and data-integrity controls including erasure coding, checksums, bit-rot protection, background healing and strong consistency

. Experience implementing checkpointing and recovery across hot and cold reboots, retention and lifecycle controls for the contracted retention period, high availability, backup and recovery, and operational/disaster-recovery deployment with inter-site synchronisation

Equivalent Technologies

. Equivalent large-scale batch or stream-processing frameworks may be considered where the candidate demonstrates transferable distributed-data-system experience Apache Airflow or an equivalent workflow-orchestration platform and other S3-compatible object stores remain relevant supporting technologies

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