Senior Data Engineer (Public Sector)

3-year contract, renewableHybrid work arrangementGoverment projectWhat Will You Do?Data Pipeline Infrastructure & ArchitectureDesign and implement scalable data architectures on cloud data platforms with high availability, security, and performanceLead development of Data Lakehouse solutionsCollaborate with stakeholders to understand requirements and translate them into technical specificationsPipeline Development & OptimisationBuild and maintain robust ETL/ELT pipelines using modern data engineering tools and frameworksOptimise data processing workflows for performance, cost-effectiveness, and reliabilityImplement automated data quality checks and monitoring systems to ensure data integrityData Systems Architecting & SolutioningDesign and architect comprehensive cloud-native Data & AI solutions aligned with business objectives and technical requirementsLead cloud migration strategies and oversee implementation of complex multi-cloud environmentsDrive innovation through integration of Data & AI capabilities into HDB's Data & AI platform product architecturesConduct technical assessments and recommend modernised approaches using cloud native technologiesMaintain architectural documentationCloud Platform OperationsLeverage Cloud Native Services to build and manage data infrastructureImplement infrastructure as code practices using TerraformEnsure compliance with security standards and data governance policiesTechnical Leadership & CollaborationMentor junior data engineers and provide technical guidance on complex challengesParticipate in architectural reviews and contribute to data strategy evolutionYou will be a Great Fit If You HaveBachelor's degree in computer science, Information Technology, Computer Engineering, or related fieldMinimum 3 years of relevant experience in data systems architecture, data systems integration, and data pipeline setup at production scaleGood understanding of cloud computing principles including infrastructure as code, containerisation, microservices architecture, cloud security frameworks, identity and access management, network architecture, and distributed systemsProven ability to translate business requirements into technical solutionsExcellent communication skills for presenting complex concepts to diverse audiencesExperience with cloud security frameworks, compliance requirements, and risk managementExperience in data domains (e.g. DataOps, Data Lakehouse) and AI/ML Domains (e.g. MLOps, LLMOps)Strong Knowledge and Hands-on experience with SQL, Python and Apache SparkHands-on experience with Apache Kafka, Airflow, or similar technologiesGood to Have:Proficiency in Amazon Web Services (AWS) servicesRelevant cloud certifications (e.g. AWS Solutions Architect Professional, AWS Data Engineer Associate) would be an advantageExperience with Data & AI cloud-native services (e.g. Amazon SageMaker Unified Studio, Amazon Quick Suite, AWS S3, AWS Glue, AWS Lake Formation, AWS Bedrock, AWS Agent Core).Familiarity with serverless computing, edge computing, and IoT architectures would be an advantage.Experience with machine learning operations (MLOps) and ML model deployment pipelinesKnowledge of data governance frameworks and metadata management toolsFamiliarity with data visualisation tools and business intelligence platforms