Data Encoder

About the role

The Lead Data Engineer is responsible for the bank's target data platform and the data engineering team. The scope includes the ingestion, processing, storage, and serving layers; batch and streaming pipelines; data contracts; governance; and SLAs for data freshness, completeness, and correctness.

Responsibilities

• Design and evolve the target lakehouse/DWH architecture, from ingestion to serving.
• Own the architecture of batch and streaming pipelines and the standards for their implementation.
• Build streaming-first integrations with banking domains using Kafka.
• Implement change data capture (CDC) from the core banking system (CBS) and other operational systems, with controls for completeness, ordering, and redelivery.
• Develop the Data Lake, ClickHouse, analytical data marts, and the serving layer for BI, ML, and AI agents.
• Design real-time data marts and streams for fraud prevention and risk management.
• Implement data contracts, a schema registry, schema compatibility rules, and a change management process.
• Ensure data lineage, a data catalog, data quality monitoring, and classification of personally identifiable information (PII).
• Define SLAs/SLOs for data freshness, completeness, and correctness, and coordinate the response to breaches.
• Develop and maintain ETL/ELT pipelines using Airflow, dbt, Spark, and Kafka.
• Optimize performance, storage and compute costs, the data lifecycle, and data consumption.
• Implement CI/CD, automated testing, and observability for data pipelines.
• Develop data mart architecture for analytics, feature stores, ML/GenAI, and RAG use cases.
• Manage the data engineering team, including planning, hiring, performance reviews, professional development, and technical mentoring.
• Collaborate with Analytics, ML, Product, Engineering, Security, and banking domain owners.

Technology context

• Kafka, schema registry, and CDC.
• Airflow, dbt, and Spark.
• ClickHouse MergeTree, S3 Data Lake, and lakehouse/DWH.
• SQL, Python, and/or Scala.
• Kubernetes and GitLab CI/CD.
• OpenTelemetry, Prometheus, Grafana, and dedicated data quality monitoring.
• Data contracts, lineage, catalogs, and PII classification.
• PostgreSQL and other operational data sources from banking domains.

GuzoGo is expanding its travel technology platform, connecting flights, global hotels, tours, and transport with local and international payment options.

We are looking for a skilled DevOps Engineer to build, manage, and optimize the cloud infrastructure powering our platform. We need someone who can automate deployments, maintain reliable production environments, strengthen infrastructure security, and ensure our systems are ready to scale.

Your Responsibilities

• Design, deploy, and maintain AWS cloud infrastructure.
• Build and manage automated CI/CD pipelines.
• Manage Docker containers and application deployment environments.
• Implement infrastructure automation and configuration management.
• Monitor system performance, availability, logs, and infrastructure health.
• Implement backup, disaster recovery, and production recovery procedures.
• Manage infrastructure security, access controls, and environment configurations.
• Troubleshoot production issues and optimize infrastructure performance and costs.
• Collaborate with development teams to improve software delivery and system reliability.

At Quantum Technology PLC

About the Role

We are seeking a hands-on DevOps Engineer to maintain secure and reliable on-premises and cloud infrastructure, own deployment and release operations, and work closely with backend developers. The role combines Linux administration, Docker operations, automation, databases, monitoring, and incident response.