Senior Data Engineer
Senior Data Engineer
We are seeking a Senior Data Engineer to support a digital transformation initiatives. This role focuses on designing, building, and maintaining scalable data solutions that enable ministries to improve data quality, accessibility, and decision-making. The ideal candidate will combine strong data engineering expertise with analytical capabilities to develop modern data pipelines, integrate diverse data sources, and deliver analytics solutions that support the delivery of digital services across government. The Data Engineer will work collaboratively with business and technical stakeholders to translate requirements into solutions and enable self-service analytics capabilities.
The Data Engineer will be responsible for designing and building scalable data pipelines across on-premises and cloud platforms, developing and optimizing data models, integrating data from multiple sources, and enhancing ETL/ELT processes through automation and performance tuning. Additionally, the role includes developing interactive Power BI dashboards and reports, analyzing datasets to identify trends and patterns, building predictive or descriptive models, and providing data-driven insights to support corporate priorities and strategic initiatives. The Data Engineer will work across two to three projects on a full-time basis, delivering iterative solutions in an Agile environment while supporting data governance and enterprise data platform management.
Qualifications
- 5 years - Experience as a Data Engineer and/or Data Analyst
- 5 years - Experience in Python (including PySpark) and SQL, applied to developing, orchestrating, and optimizing enterprise-grade ETL/ELT workflows in a large-scale cloud environment
- 4 years - Business Intelligence and Executive Reporting: Built executive dashboards, KPI reporting, self-service BI solutions and business performance reporting
- 4 years - Cloud or Hybrid Data Platforms: Experience with Cloud modernization, or hybrid/cloud data platform implementations
- 4 years - Data Warehouse and Lakehouse Design: Enterprise data warehouse or lakehouse projects using Star/Snowflake schemas, fact/dimension modeling
- 4 years - Knowledge of ETL processes and tools, with hands-on experience designing and implementing data pipelines for transforming and loading data from multiple sources into data warehouses
- 2 years - Data Migration and Modernization: Plan, execute, validate, and support data migrations across on-premises, cloud, and cross-database environments
- Bachelor degree in Computer Science, Information Technology, Engineering, Mathematics, Statistics, Data Science, or a related field
Nice to Have
- 2 years - Experience supporting enterprise-scale applications in public sector or mixed delivery environments
- 2 years - Experience in DevOps, CI/CD, and Infrastructure as Code: Designing, implementing, or maintaining CI/CD pipelines and Infrastructure as Code practices to support automated deployment, configuration, and management of cloud-based data platforms and services
- 1 year - Modern data technology: Experience in modern data technologies such as Microsoft Fabric, Databricks, Spark, Delta Lake, or similar lakehouse and big data platforms
- 1 year - Experience in AI-Assisted Development Tools and Practices: Leverage AI-assisted development tools to improve productivity, code quality, documentation, testing, and data engineering workflows while applying appropriate review and quality controls
We are seeking a Senior Data Engineer to support a digital transformation initiatives. This role focuses on designing, building, and maintaining scalable data solutions that enable ministries to improve data quality, accessibility, and decision-making. The ideal candidate will combine strong data engineering expertise with analytical capabilities to develop modern data pipelines, integrate diverse data sources, and deliver analytics solutions that support the delivery of digital services across government. The Data Engineer will work collaboratively with business and technical stakeholders to translate requirements into solutions and enable self-service analytics capabilities.
The Data Engineer will be responsible for designing and building scalable data pipelines across on-premises and cloud platforms, developing and optimizing data models, integrating data from multiple sources, and enhancing ETL/ELT processes through automation and performance tuning. Additionally, the role includes developing interactive Power BI dashboards and reports, analyzing datasets to identify trends and patterns, building predictive or descriptive models, and providing data-driven insights to support corporate priorities and strategic initiatives. The Data Engineer will work across two to three projects on a full-time basis, delivering iterative solutions in an Agile environment while supporting data governance and enterprise data platform management.
Qualifications
- 5 years - Experience as a Data Engineer and/or Data Analyst
- 5 years - Experience in Python (including PySpark) and SQL, applied to developing, orchestrating, and optimizing enterprise-grade ETL/ELT workflows in a large-scale cloud environment
- 4 years - Business Intelligence and Executive Reporting: Built executive dashboards, KPI reporting, self-service BI solutions and business performance reporting
- 4 years - Cloud or Hybrid Data Platforms: Experience with Cloud modernization, or hybrid/cloud data platform implementations
- 4 years - Data Warehouse and Lakehouse Design: Enterprise data warehouse or lakehouse projects using Star/Snowflake schemas, fact/dimension modeling
- 4 years - Knowledge of ETL processes and tools, with hands-on experience designing and implementing data pipelines for transforming and loading data from multiple sources into data warehouses
- 2 years - Data Migration and Modernization: Plan, execute, validate, and support data migrations across on-premises, cloud, and cross-database environments
- Bachelor degree in Computer Science, Information Technology, Engineering, Mathematics, Statistics, Data Science, or a related field
Nice to Have
- 2 years - Experience supporting enterprise-scale applications in public sector or mixed delivery environments
- 2 years - Experience in DevOps, CI/CD, and Infrastructure as Code: Designing, implementing, or maintaining CI/CD pipelines and Infrastructure as Code practices to support automated deployment, configuration, and management of cloud-based data platforms and services
- 1 year - Modern data technology: Experience in modern data technologies such as Microsoft Fabric, Databricks, Spark, Delta Lake, or similar lakehouse and big data platforms
- 1 year - Experience in AI-Assisted Development Tools and Practices: Leverage AI-assisted development tools to improve productivity, code quality, documentation, testing, and data engineering workflows while applying appropriate review and quality controls