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Full Time
Some careers shine brighter than others.
If you re looking for a career that will help you stand out, join HSBC and fulfil your potential. Whether you want a career that could take you to the top, or simply take you in an exciting new direction, HSBC offers opportunities, support and rewards that will take you further.
HSBC is one of the largest banking and financial services organisations in the world, with operations in 64 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realise their ambitions.
We are currently seeking an experienced professional to join our team in the role of Senior Consultant Specialist.
In this role, you will:
Design & Develop Observability Solutions: Build and enhance telemetry pipelines for logs, metrics, and traces using industry-standard tools (kafka, OpenTelemetry, Splunk)
Instrument Applications: Implement observability best practices in infrastructure, applications and platforms.
Design and Implement machine learning models to analyze logs, metrics and traces for anomaly detection, predictive failure analysis and root cause analysis.
Monitor & Analyze System Performance: Build and Develop real-time data visualization dashboards and alerts to track system health, detect anomalies, and support real-time troubleshooting.
Work with Event-Driven Architectures: Integrate observability with messaging systems like Kafka, RabbitMQ, or Pulsar for real-time monitoring.
Collaborate Across Teams: Work closely with SREs, DevOps, and development teams to improve system reliability and incident response.
Security & Compliance: Ensure observability data is securely stored and compliant with relevant regulations (GDPR, HIPAA, etc. ).
Optimize Performance: Conduct root cause analysis and improve system observability to reduce downtime and improve response times.
To be successful in this role, you should meet the following requirements:
Data Science & Machine Learning experience: Hands-on proficiency in Python, TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy.
Extensive knowledge of ETL techniques: Data extraction, transformation, and loading using Apache Airflow, Apache NiFi, Spark or similar tools
Observability Stack: Hands-on experience with Prometheus, Grafana, ELK Stack, Loki, OpenTelemetry, Jaeger, or Zipkin.
Experience with Time-Series Analysis, Predictive Analytics and AI-driven Observability.
Cloud & Infrastructure: Experience with AWS, Azure, or GCP observability services (e. g. , CloudWatch, Azure Monitor).
Distributed Systems & Microservices: Understanding of Kubernetes, Docker, and Service Mesh technologies (Istio, Linkerd).
Event-Driven Architectures: Experience with Kafka, RabbitMQ, or other message brokers.
Database & Storage: Familiarity with time-series databases (InfluxDB, VictoriaMetrics) and NoSQL/SQL databases.
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