3352 Data Engineer (Expert)

SUMMARY:
ESSENTIAL SKILLS:

• Hands-on experience with Kafka and event streaming platforms for real-time data movement.
• Proven experience with API integration patterns, webhooks and event/webhook ingestion.
• Strong proficiency in Python for data engineering, ingestion pipelines and automation.
• Solid competence with enterprise databases and query languages, with practical experience with database performance tuning and query optimisation for OLTP/operational workloads.
• Experience in data modelling to design schemas and standardized data representations.
• Experience with schema registries and contract-first designs (Avro, Protobuf) to manage producer/consumer compatibility.
• Strong understanding and practice of data quality techniques and tooling to ensure trusted data.
• Knowledge of metadata management and cataloguing to support discoverability and lineage.
• Familiarity with ETL/ELT patterns and best practices for performant, reliable data pipelines.
• Ability to normalise and correlate data across multiple sources (CMDB, identity, security tooling).
• Design and operate idempotent pipelines with retry, replay and compensation mechanisms.

• Experience with Java for stream processing or connector development.
• Awareness of frontend frameworks (e.g., Angular) to better understand downstream consumers.
• Familiarity with infrastructure automation and IaC (e.g., Terraform) to deploy integration components.
• Experience operating container platforms and orchestration (Kubernetes) for scalable stream processing.
• Experience with NoSQL/document stores such as MongoDB for operational data needs.
• Familiarity with enterprise systems like SAP and working with their integration interfaces.
• Experience with big data ecosystems (CDH/Hadoop) and distributed storage/processing.
• Working knowledge of Azure Synapse or similar data platform services for integrated data processing.
• Observability for streaming: experience with metrics, tracing and logging for pipelines (Prometheus, Grafana, OpenTelemetry).
• Experience with connector ecosystems and managed services (Kafka Connect, Confluent Cloud, managed Kafka).
• Knowledge of message delivery semantics, partitioning strategies and capacity planning for high-throughput pipelines.

POSITION INFO:
ROLE & RESPONSIBILITIES: Design, build and operate operational data integration solutions focused on making enterprise data available, trusted and consumable. Ingest and stream data from Zero Trust data sources (CMDB, identity systems, security tooling) into operational pipelines rather than analytics stores. Build and maintain Kafka topics, producers\/consumers, connectors and streaming applications to enable realtime flows. Implement API-based integrations, webhook listeners and file ingestion solutions to capture operational events. Develop robust ETL\/ELT and stream processing logic to normalise, correlate and enrich data across sources. Ensure pipelines are idempotent and resilient (retries, replay, backpressure and compensation strategies). Apply data modelling and metadata practices to ensure consistent schemas and discoverability. Implement and monitor data quality checks, anomaly detection and validation rules; drive remediation where needed. Maintain data lineage, access control and security practices to meet governance and compliance requirements. Collaborate with automation and orchestration teams to ensure streamed operational data feeds automation workflows and runbooks. Own pipeline alerting, runbooks, and participate in incident response\/on-call rotations Troubleshoot production issues, perform root cause analysis and implement long-term reliability improvements. Build testable pipelines with unit\/integration tests, contract tests and CI\/CD deployment pipelines for streaming workloads Data Quality Gates: enforce automated quality checks early in pipelines (validation, schema checks, anomaly detection) and block or quarantine bad data. Performance & Cost Awareness: implement efficient partitioning, batching and resource usage patterns while tracking cost and throughput trade-offs. Security & Privacy by Design: apply least-privilege, secrets management, encryption in transit and at rest, and data masking\/anonymisation where required. Drive architectural decisions and define integration best practices QUALIFICATIONS\/EXPERIENCE: Extensive hands-on experience (typically 6+ years) in data engineering, integration or streaming roles with demonstrable production experience. Proven track record building and operating streaming platforms (Kafka) and API-based integrations, with strong Python\/Java and enterprise databases and query languages skills. Strong analytical thinking, curiosity about data, attention to detail, structured problem solving and ownership - able to figure things out and drive topics to completion. Submit your CV to: and Subject line Role title