Role: Data Engineering Tech Lead

Location: Sheffield (3 days onsite/2 days remote)

Duration: 6 months + Extension

Budget: £350 - £400 per day, Inside IR35

THIS PROJECT IS INSIDE IR35

Key Responsibilities:

• Design, implement, and maintain data pipelines to ingest and process OpenShift telemetry (metrics, logs, traces) at scale.
• Stream OpenShift telemetry via Kafka (producers, topics, schemas) and build resilient consumer services for transformation and enrichment.
• Engineer data models and routing for multi-tenant observability; ensure lineage, quality, and SLAs across the stream layer.
• Integrate processed telemetry into Splunk for visualization, dashboards, alerting, and analytics to achieve Observability Level 4 (proactive insights).
• Implement schema management (Avro/Protobuf), governance, and versioning for telemetry events.
• Build automated validation, replay, and backfill mechanisms for data reliability and recovery.
• Instrument services with OpenTelemetry; standardize tracing, metrics, and structured logging across platforms.
• Use LLMs to enhance observability capabilities (eg, query assistance, anomaly summarization, runbook generation).
• Collaborate with platform, SRE, and application teams to integrate telemetry, alerts, and SLOs.
• Ensure security, compliance, and best practices for data pipelines and observability platforms.
• Document data flows, schemas, dashboards, and operational runbooks.

Required Skills:

• Hands-on experience building streaming data pipelines with Kafka (producers/consumers, schema registry, Kafka Connect/KSQL/KStream).
• Proficiency with OpenShift/Kubernetes telemetry (OpenTelemetry, Prometheus) and CLI tooling.
• Experience integrating telemetry into Splunk (HEC, UF, sourcetypes, CIM), building dashboards and alerting.
• Strong data engineering skills in Python (or similar) for ETL/ELT, enrichment, and validation.
• Knowledge of event schemas (Avro/Protobuf/JSON), contracts, and backward/forward compatibility.
• Familiarity with observability standards and practices; ability to drive toward Level 4 maturity (proactive monitoring, automated insights).
• Understanding of hybrid cloud and multi-cluster telemetry patterns.
• Security and compliance for data pipelines: secret management, RBAC, encryption in transit/at rest.
• Good problem-solving skills and ability to work in a collaborative team environment.
• Strong communication and documentation skills.