Description

• Design, develop, and maintain scalable data pipelines across on-premises and cloud platforms (Azure, AWS, GCP)
• Build and optimize dimensional data models (star and snowflake schemas) for reporting and analytics
• Develop and maintain ETL/ELT processes ensuring performance, reliability, and scalability
• Integrate data from multiple sources including SQL, NoSQL, APIs, and flat files
• Develop and manage end-to-end data workflows using SSIS and Azure Data Factory
• Implement monitoring, logging, error handling, and troubleshooting for data pipelines
• Manage data warehouses and data lakes with strong focus on governance, security, and access control
• Automate deployments and testing using CI/CD pipelines and version control (Git)
• Collaborate with stakeholders to translate business requirements into technical solutions
• Deliver curated datasets and data marts for self-service analytics
• Analyze datasets to identify trends, patterns, anomalies, and actionable insights
• Develop dashboards and reports using Power BI (including DAX)
• Build descriptive and predictive models using Python, R, or statistical methods
• Communicate insights clearly to both technical and non-technical stakeholders
• Support agile delivery of analytics and data solutions
• Ensure data quality, governance, and security across systems
• Strong hands-on experience in SQL, Python and/or R
• Solid understanding of data architecture and ETL/ELT concepts
• Bachelor’s degree in Computer Science, IT, or related field
• Minimum 5+ years of experience in data engineering and/or data analytics
• Experience working with cloud and on-premises data environments
• Proven experience in data migration across systems
• Public Sector experience is mandatory

Nice to Have

• Experience in application development (object-oriented or functional programming)
• Familiarity with PostgreSQL, MongoDB, or other cloud-native databases
• Exposure to AI/ML tools, frameworks, or workflows
• Experience working in large-scale, complex enterprise environments
• Strong exposure to advanced analytics or data science practices
• Experience promoting data literacy and enabling self-service analytics culture

Key Skills

Education

Bachelor's degree