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Senior data engineer (flink)

London
N Consulting Global
Data engineer
Posted: 20h ago
Offer description

Job Description

Senior data engineer (Apache Flink)

Role overview

You will bring deep hands-on expertise in production Flink on AWS, working closely with a senior FT engineer

and AWS stakeholders. A key part of the role is knowledge transfer through pairing, reviews and clear

documentation so the capability can be supported and extended by FT.

Responsibilities

● Design and implement stateful stream-processing jobs in Apache Flink (primarily Java), to process user

interaction events and produce near real-time outputs for downstream services.

● Integrate Flink with Kafka/AWS MSK, S3 and the chosen online store (MongoDB/MongoDB Atlas).

● Own streaming non-functional requirements: correctness, fault tolerance, checkpointing/recovery,

backpressure handling, and performance tuning.

● Define and implement production readiness: observability (metrics/logs/tracing), alerting, dashboards

and runbooks.

● Support CI/CD and infrastructure-as-code practices to deploy and operate Flink workloads safely in AWS.

● Enable the team via knowledge transfer (pairing, design/code reviews, documentation and handover).

Skills and experience

Essential

● Strong experience building and operating production Apache Flink applications (event-time concepts,

windows/watermarks, state, checkpointing and fault tolerance).

● Hands-on AWS experience operating streaming/data workloads (IAM, networking/VPC basics,

deployment, observability and incident troubleshooting).

● Experience integrating Flink with Kafka (including AWS MSK) and cloud services/storage (e.g., S3).

● Highly proficient in Java and Python (production experience required).

● Strong software engineering fundamentals: clean, maintainable code; pragmatic testing; effective code

review.

● Comfort mentoring/pairing with engineers to up-skill the team.

Desirable

● Experience with Amazon Managed Service for Apache Flink and/or running Flink on EKS/ECS.

● Experience with MongoDB or MongoDB Atlas for low-latency, online-serving use cases.

● Infrastructure-as-code (CloudFormation) and modern observability tooling (CloudWatch, Grafana,

OpenTelemetry, Splunk).

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