Software Engineer in England

We are looking for a Software Engineer (AWS) to join our AI & Data Ops team. In this role, you will take ownership of two core systems: our internal Python library used across the organisation for data science workflows, and a production data validation system — a system embedded in AWS. This is a hands‑on engineering role. You will write Python daily, own production cloud infrastructure, and collaborate closely with data scientists, devops engineers and analysts to ship reliable, well‑tested systems.

Your responsibilities would include:

• As part of the AI & Data Ops team, you will build and maintain internal software that supports the product team with building and deploying KPI trackers.
• Co‑own and maintain the internal Python library used across the organisation for data science workflows, including versioning, releases, and API design.
• Own and operate the Anomaly Detection Framework — a production system built on AWS that detects anomalies before they reach client facing systems.
• Write and maintain AWS Lambda handlers and serverless functions in Python.
• Write Terraform to add, modify, or configure AWS resources (Lambda, Step Functions, S3 buckets, IAM policies, DynamoDB tables, SQS queues), submitting PRs for DevOps review.
• Debug Step Functions executions, investigate CloudWatch logs, and resolve production issues.
• Write and maintain GitHub Actions workflows for CI/CD, automated testing, and package releases.
• Write unit, integration, and regression tests to ensure library and infrastructure stability.
• Conduct code reviews and enforce coding standards for contributions to shared codebases.
• Triage and resolve bug reports and feature requests from internal library users.
• Collaborate with data scientists and analysts to translate requirements into production‑ready code.

Required Qualifications Experience:

• 2–4 years in software engineering, data engineering, or a related field.
• Proven track record of independently owning and delivering data projects.

Python:

• Strong Python proficiency with clean, well‑tested, production‑quality code.
• Experience contributing to and maintaining shared Python libraries or packages.
• Proficient with the data science stack: pandas, numpy, matplotlib, scikit‑learn.
• Familiarity with ORM patterns (e.g., SQLAlchemy) and database connectivity in Python.
• Experience with data serialization formats (JSON, HDF5, Parquet).
• Strong understanding of testing frameworks (pytest, unittest) and test‑driven development.

AWS & Cloud:

• Hands‑on experience with core AWS services: Lambda, Step Functions, S3, SQS, DynamoDB, ECS, CloudWatch.
• Comfortable writing production Lambda handlers and debugging serverless architectures.
• Experience with event‑driven architectures (SQS triggers, S3 notifications, Step Functions orchestration).
• Ability to read and write Terraform for AWS resource provisioning.

Other Required Skills:

• Strong Git skills including branching strategies and code review workflows.
• Experience writing CI/CD pipelines (GitHub Actions or similar).
• A collaborative mindset and strong communication skills.
• Self‑motivated with ability to work autonomously.

Nice to Have Skills:

• Having experience in at least one of the following areas would be a strong plus:
• Statistical anomaly detection methods (Z‑scores, IQR, CUSUM, control charts).
• Time series analysis and forecasting techniques (Prophet, ARIMA, exponential smoothing).
• Machine learning for anomaly detection (Isolation Forest, autoencoders, Bayesian changepoint detection).
• Familiarity with Slack APIs or similar messaging platform integrations.
• API Gateway for webhooks and callback integrations.
• Docker containerisation for packaging and deploying data pipelines.
• Grafana or similar dashboarding and observability tools.
• Experience with data quality and observability frameworks.
• Advanced SQL and database optimisation.
• Understanding of or strong interest in financial markets and business metrics.