Consultant

Data & Analytics

The aim is to state the overall significance of the job from the organization’s perspective.

To design, develop, maintain, and support enterprise data integration solutions that enable reliable and scalable data movement across business systems and analytical platforms. The role is responsible for developing ETL processes, managing data pipelines, supporting reporting and analytics requirements, and ensuring operational continuity of critical data integration services while maintaining data quality, availability, and performance across the enterprise data ecosystem.

This section describes the principal outputs required from the job.

ETL Development & Enhancement

Design, develop, and maintain ETL processes to support enterprise reporting and analytics requirements.

Develop scalable and reusable data integration components and workflows.

Implement enhancements to existing ETL solutions to improve performance and reliability.

Ensure ETL solutions comply with established data engineering standards and practices.

Data Integration Management

Develop and maintain integrations between enterprise applications, databases, external sources, and analytical platforms.

Support data exchange requirements across multiple systems and business functions.

Ensure reliable movement and transformation of data across integration environments.

Troubleshoot and resolve integration-related issues and failures.

Data Pipeline Operations

Monitor, support, and maintain production data pipelines and scheduled processing jobs.

Ensure timely execution and completion of critical data processing activities.

Investigate operational incidents affecting data pipelines and implement corrective actions.

Support operational continuity and service availability requirements.

Data Quality & Validation

Implement validation controls and data quality checks throughout data integration processes.

Identify and resolve data inconsistencies, anomalies, and processing issues.

Support initiatives aimed at improving data accuracy, completeness, and consistency.

Collaborate with stakeholders to address data quality concerns.

Data Modeling & Database Support

Support the design and maintenance of data models that satisfy reporting and analytical requirements.

Develop and optimize database queries, views, and supporting structures.

Ensure database performance and scalability requirements are achieved.

Contribute to enterprise data architecture initiatives when required.

Analytics & Reporting Enablement

Support business intelligence and reporting initiatives through trusted and accessible data sources.

Prepare and maintain datasets required for dashboards, analytics, and business reporting.

Collaborate with analysts and reporting teams to understand data requirements.

Ensure data availability supports timely business decision-making.

Stakeholder Engagement & Requirements Support

Work closely with business users, analysts, and technology teams to understand integration requirements.

Translate business requirements into technical data solutions.

Support project teams through technical expertise in data integration and engineering.

Provide ongoing support for data-related requests and enhancements.

Continuous Improvement & Automation

Identify opportunities to automate manual data integration and processing activities.

Improve efficiency, reliability, and maintainability of data engineering solutions.

Support adoption of best practices, development standards, and emerging technologies.

Contribute to continuous improvement initiatives across the Data & Analytics function.

Policies, Processes & Procedures

Follow all relevant departmental policies, processes, standard operating procedures, and instructions so that work is carried out in a controlled and consistent manner.

Comply with all relevant safety, quality, and environmental management policies, procedures, and controls to ensure a healthy and safe work environment.

Information Security

Comply with all relevant information security practices and standards to ensure data integrity and confidentiality.

4–6 years of experience in Data Engineering, ETL Development, Data Integration, Data Warehousing, Business Intelligence, or related domains.

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