5 of 5 Confluent Jobs in the City of London

flows and manages API calls across Pega, Vlocity, and external systems Machine Learning Models via Vertex AI (GCP) AWS Glue + Lambda + Step Functions : Batch ETL workflows Kafka (Confluent Cloud) : Real-time feature streams ingestion Kinesis Streams + Firehose : Traceability and telemetry routing Cloud Storage (S3, GCP buckets) : Configuration, logs, traceability data Envoy Proxy + ALB + WAF : TLS More ❯

Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally AWS), Kubernetes, and relevant SDKs (e.g., boto3, confluent-kafka). Experience deploying ML models in production using REST APIs, microservices, and Docker containers. Understanding of NLP, LLMs, and prompt engineering techniques. Proficient in version control, CI/CD More ❯

direction across entire programmes and client estates. Key Responsibilities Senior Data Architects: Lead the design and delivery of cloud-native data solutions using modern platforms (e.g. Databricks, Snowflake, Kafka, Confluent) Architect data lakes, lakehouses, streaming pipelines, and event-driven architectures Oversee engineering teams and collaborate with analysts and QA functions Translate complex requirements into scalable, robust data products and platforms More ❯

and emerging technologies Essential Skills Technical Expertise: 2 to 3 years Java development - enterprise-level experience required C++ knowledge or strong motivation to master high-performance languages Kafka/Confluent - real-time data streaming experience Agile methodologies (Scrum, XP, Kanban) - collaborative delivery experience Testing mastery : BDD, TDD, unit, integration, automation testing Git version control and modern development workflows DevOps principles More ❯

key metrics to ensure platform performance, user engagement, and operational efficiency. What We're Looking For: Deep expertise in real-time data processing and streaming technologies (e.g. Kafka, Flink, Confluent, Redis). Experience with data platforms and pipelines in cloud environments (Databricks on AWS, Glue, Azure Data Factory). A track record of hands-on data architecture in fast-paced More ❯