Job Description
The Data Analytics Specialist is responsible for designing, developing, and operating the analytics layer of the organisation's enterprise data platform, hosted on Oracle Cloud Infrastructure (OCI). The role focuses on transforming operational data into trusted analytical datasets, dashboards, and reusable data assets that enable self‑service reporting and data‑driven decision‑making. This position also contributes to business data modelling, KPI definition, and the creation of reporting solutions that establish a single source of truth across the organisation. The specialist works closely with business teams and IT stakeholders to deliver scalable, governed, and AI‑ready analytical assets aligned with the organisation's data strategy.
Data Analytics Platform Design
Design and maintain the analytics architecture of the enterprise data platform.
Structure analytical datasets in Oracle Autonomous Data Warehouse (ADW).
Build and maintain semantic data models supporting dashboards and reporting tools.
Ensure analytical solutions provide a unified, authoritative view of business data.
Business Data Modelling
Define and structure core business entities and their relationships.
Develop data models supporting consistent KPI definitions across reporting tools.
Collaborate with business stakeholders to validate logic and metrics.
Dashboard & Analytics Development
Design and deliver interactive dashboards using Oracle Analytics Cloud (OAC) and Microsoft Power BI.
Develop standardised dashboards for key organisational use cases.
Create reusable datasets, visualisations, and dashboard templates.
Ensure dashboards are intuitive, reliable, and aligned with business needs.
Self‑Service Reporting Enablement
Enable business units to build and customise their own dashboards through self‑service BI features.
Develop shared datasets and semantic layers accessible to business users.
Maintain a library of BI templates and curated reporting datasets.
Provide training and support to promote effective use of analytics tools.
Data Quality & Governance
Implement processes ensuring data quality, reliability, and consistency.
Monitor data quality metrics and identify anomalies.Maintain business definitions and metadata using a business glossary and data catalog.
Ensure accurate data lineage and documentation across analytical datasets.
Support compliance with data governance and regulatory requirements (e.g., GDPR).
Data Integration for Analytics
Collaborate with IT teams to integrate data from multiple enterprise systems.
Support ingestion pipelines using OCI Data Integration and Oracle Data Transform.
Validate data pipelines to ensure consistent data availability for analytics.
Data Products & API Enablement
Develop reusable analytical datasets consumed by dashboards, APIs, and analytical applications.
Support the development of data APIs through the organisation's API gateway.Ensure APIs and dashboards rely on consistent business definitions.
AI‑Ready Data Foundation
Prepare structured, governed datasets to enable advanced analytics and future AI initiatives.
Maintain documentation, metadata, and lineage for AI reliability.
Collaborate with data science teams to provide curated datasets for experimentation.
Platform Monitoring & Optimisation
Monitor analytics workloads in OAC and ADW.
Optimise queries, datasets, and dashboards for performance.
Support operational monitoring using OCI observability tools.
Qualifications
10+ years of experience in data analytics, BI, or analytics engineering.
5+ years of experience with Oracle technologies (PL/SQL, SQL, architecture, tuning).
Strong expertise in enterprise analytics platform implementations.
Proven experience working with business stakeholders to define reporting requirements and KPIs.
Experience with cloud‑based data platforms.
Advanced skills in designing semantic models for BI tools.
Strong knowledge of data visualisation and dashboard design.
Hands‑on experience with Oracle Analytics Cloud (OAC).
Experience with OCI Data Integration.
Experience implementing data catalogs or data governance frameworks.
Exposure to AI/ML data preparation.
Knowledge of API‑based data access and data products.
Fluency in English.
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