AWS Data Engineer

Roles & Responsibilities

• Engage with business units to understand data, reporting, KPI, and analytics requirements.
• Facilitate requirements workshops and translate business needs into clear data specifications.
• Act as the liaison between business stakeholders and the technical data platform team.
• Design and develop data transformation logic for reporting and analytics datasets.
• Build and maintain data models in Amazon Redshift or the curated/consumption zone of the Data Lake.
• Ensure reporting datasets are accurate, consistent, and complete through data quality checks and validation.
• Design, develop, and maintain interactive Tableau dashboards and reports using Amazon Redshift or S3.
• Develop near-real-time dashboards, ad-hoc analysis views, and scheduled reports based on business needs.
• Improve dashboard usability based on stakeholder feedback and evolving requirements.
• Maintain data definitions, business glossary terms, dashboard logic, data sources, transformation logic, and report specifications in the AWS Glue Data Catalogue.
• Support self-service analytics by enabling business users to discover and access data independently.

Requirements

Essential

• Minimum 3 years of experience in data engineering, business intelligence, or data analytics.
• Strong SQL skills for querying, transformation, and data modelling.
• Hands-on experience with Tableau or equivalent BI tools such as Power BI or QuickSight.
• Experience with cloud data platforms, preferably AWS, Amazon Redshift, S3, and AWS Glue.
• Strong stakeholder engagement and communication skills with the ability to translate business requirements into technical specifications.
• Experience with analytical data modelling, including star schema and dimensional modelling.

Preferred

• Familiarity with Python for data transformation and automation.
• Experience with AWS Glue Data Catalogue or similar metadata management tools.
• Exposure to Salesforce or other SaaS data sources.
• Experience in a government or public sector environment.
• Understanding of data governance and data quality principles.