Operate DataPipes (EKS + Airflow) for ingestion orchestration, ensuring high availability and version-controlled configurations via IaC (CloudFormation/CDK).
Maintain & enhance logging, monitoring, observability & DevOps automation via modern tools such as CloudWatch, Splunk, PagerDuty, Slack, ServiceNow, Snowflake observability features.
Maintain and manage the observability of infrastructure environment of Data Engineering, including monitoring, logging, alerting, notification and so on, focusing on the monitor system performance and proactively identify and resolve issues. Optimize system performance and resource utilization.
Work closely with cross-functional teams to understand business needs and deliver data-driven insights.
Provide technical support, data ops environment on-call and training to team members and stakeholders on data operation tools and best practices.
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Own the data ops CI/CD service and its deployment templates.
Onboard new projects and repositories onto the CD automation; own the standard folder structure template and enforce its use. Maintain build and deployment reliability: pipeline runtime, failure rate, and diagnosability of failed builds.
Drive continuous improvement of the pipeline: build caching, container image hygiene, secret handling, environment promotion, and rollback paths.
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Partner with business product owners, technology teams, and senior stakeholders to provide trusted technical advice, influence strategic decisions, and foster adoption of data science solutions across the organisation.
Contribute to the growth of the Data Science community by sharing knowledge, mentoring team members, promoting best practices, and bringing insights from internal and external projects to continuously improve capabilities and business outcomes.
Design, build, and enhance data science and AI products that contribute to a Unified Revenue Growth Management (RGM) Engine, enabling the evolution from centralized insights to AI-powered decision-making and execution.
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You will design and implement the platform's identity, access and security model across AWS IAM, Kubernetes RBAC and service identities, working with the storage access and security teams.
You will build the observability, alerting, capacity planning, and incident tooling for the platform. You will contribute to the SRE practice, which includes SLOs, runbooks, on-call, and post-incident reviews. You will reduce toil and MTTR.
You will own compute cost efficiency: instance and storage strategy, spot and right-sizing, bin-packing, idle reclamation, and cost attribution back to tenants.
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Design, measure, and recommend A/B tests and multivariate experiments, including layout optimisation, UI/UX efficacy, algorithm effectiveness, and API performance.
Analyse clickstream and transactional data to uncover insights on user behaviour and guide product metrics. You will manage instrumentation for all feature releases within assigned tech families within the bank.
Develop self-serve solutions for partners that are scalable and automated to handle a product environment.
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Build and maintain People metrics, scorecards, and dashboards across the employee lifecycle, covering engagement, productivity, skills, and cost, designed for usability by non-technical audiences and not just analytical accuracy.
Design and ship self-service tools and workflows, including integrations with internal platforms such as Valet and Cortana, that enable managers and leaders to conduct their own people analysis without PSI mediation.
Transform existing People assets (e.g. the People Impact Card) from static summaries into automated, insight-driven outputs with actionable recommendations and just-in-time nudges.
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Strong understanding of B2B business environment, needs and conditions and proven knowledge of digital marketing
Secure knowledge on visualization platforms that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics via dashboards. (e.g. Power BI preferred, Tableau, SAC)
Proven experience in assembling large, complex data sets that meet functional / non-functional business requirements.
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Providing solutions to problems that apply across multiple teams is also a key expectation.
Expert proficiency in SAP Data Migration is required. Expert proficiency in Data Migrations and advanced proficiency in Syniti ADM for SAP are suggested.
Lead the design and optimization of scalable data migration strategies to enhance system integration and performance.
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