Junior dataops engineer

As a Data Ops Engineer at 24i, working within the Personalization team, you will be a member of a collaborative and innovative engineering team. Reporting to the Backend Engineering Lead, you will have a hands‑on role throughout the full software development lifecycle, contributing to the development and operation of the cloud‑based platform that powers our personalization, recommendations, and analytics capabilities. The role combines data engineering, backend development, and cloud infrastructure, with a particular focus on building and operating reliable data pipelines and services. You will work with large and diverse datasets, helping ensure that data is ingested, processed, monitored, and made available efficiently and reliably across the platform. You will also work closely with teams across the wider 24i organization, helping provide the data and services required for client performance reporting, recommendation models, personalization, and analytics. As a guide, you will have several years of experience delivering production software and data systems. We value engineers with strong foundations in data and backend engineering who are also comfortable working across engineering boundaries when required.

Key Responsibilities
Design, build, and maintain reliable data ingestion and processing pipelines supporting analytics, personalization, and recommendation use cases. Work with structured and semi-structured datasets across cloud-based storage and processing systems. Develop and maintain data orchestration workflows, ensuring that dependencies, retries, failures, and recovery are handled reliably. Contribute to data modelling and transformation processes that make data efficient and practical for downstream consumers. Help ensure the quality, consistency, and reliability of data as it moves through the platform. Identify and address performance, scalability, and cost issues within data processing workloads. Backend & Platform Engineering Design, develop, and maintain Python-based backend services and integrations supporting the Personalization platform. Quickly understand existing codebases in order to analyse behaviour, fix issues, and implement new functionality. Write high-quality, maintainable code that meets both functional and non-functional requirements. Refactor and improve existing systems while preserving expected behaviour and maintaining backwards compatibility where required. Design solutions based on product requirements and user stories, communicating technical approaches, effort, trade-offs, and risks with the rest of the team. Cloud, Deployment & Observability Develop and operate services and data workloads running in cloud environments, primarily AWS. Contribute to cloud infrastructure and deployment processes, including Infrastructure as Code and CI/CD pipelines. Build and improve observability across services and data pipelines, using logging, metrics, tracing, and alerting to understand system behaviour and diagnose issues. Contribute to the team's use of modern observability standards and tooling, such as Open Telemetry. Help ensure that changes can be deployed safely and reliably across development, staging, and production environments. Quality & Collaboration Design and implement appropriate unit, integration, and functional tests to ensure that systems are fit for purpose. Review other team members' work and provide constructive feedback through code and design reviews. Diagnose and resolve issues across data pipelines, backend services, infrastructure, and customer environments. Identify opportunities to improve our architecture, development lifecycle, tooling, reliability, and engineering practices. Support less experienced team members through code reviews, technical discussions, documentation, and sharing of engineering best practices. Plan and prioritise your work effectively and collaborate closely with other members of the engineering team. Client Data & Integrations Work with both new and existing clients, as well as internal 24i teams, to onboard and integrate data into the Personalization platform. Investigate data quality, integration, and platform issues encountered during onboarding and ongoing operation. Support existing integrations as client requirements and platform capabilities evolve. Skills and Requirements Must Have Strong Python development skills, including experience building production backend and/or data systems. Strong SQL skills and experience working with analytical or operational datasets. Experience designing, building, or maintaining data pipelines and data processing workflows. Understanding of data modelling, transformation, and data quality principles. Hands‑on experience developing and operating systems in a cloud environment, preferably AWS. Experience with workflow orchestration and the operational challenges of running data pipelines reliably. Experience implementing and operating observability for production systems using logging, metric