Data Engineer (Data Engineering & Analytics) - A26321

Activate Interactive Pte Ltd (“Activate”) is a leading technology consultancy headquartered in Singapore with a presence in Malaysia and Indonesia. Our clients are empowered with quality, cost-effective, and impactful end-to-end application development, like mobile and web applications, and cloud technology that remove technology roadblocks and increase their business efficiency.We believe in positively impacting the lives of people around us and the environment we live in through the use of technology. Hence, we are committed to providing a conducive environment for all employees to realise their full potential, who in turn have the opportunity to continuously drive innovation.We are searching for our next team members to join our growing team.If you love the idea of being part of a growing company with exciting prospects in mobile and web technologies that create positive impact on people’s lives, then we would love to hear from you.Co-Development Business Unit is looking for Data Engineer (Data Engineering & Analytics)This is a 1 - year contract role.Internal Code: A26321Digital Excellence & Products Division (DXD) is a GovTech team within the Ministry of Education (MOE). DXD sits at the intersection of technology, design, and education, building meaningful products, platforms, and digital services that improve teaching, learning, school operations, and the experience of students, teachers, and school leaders.We are looking for a DevSecOps & Engineering Enablement Engineer to establish and operate a consistent, secure, and reliable process for moving code from development to production for the future SSOE platform.You will centrally manage the tools, pipelines, standards, and automation that engineering teams use to build, test, review, secure, and deploy their code.The objective is to ensure that code progressing towards production is not only deployed successfully, but is also functionally working, secure, tested, and of the required quality. Relevant security, testing, and quality gates should be built directly into the delivery process and applied consistently across engineering teams.You will also drive the responsible use of AI within the software development lifecycle, including AI-assisted code review, testing, security analysis, documentation, and engineering feedback.What will you do?As a Data Engineering & Analytics Engineer, you will own the data lifecycle from source systems through ingestion, transformation, modelling, quality, and serving.You will build pipelines that extract and ingest data from enterprise and operational systems, transform it into consistent and trusted datasets, and make that data available to applications, dashboards, reporting, analytics, and machine-learning use cases.You will work closely with the Logging & Data Platform Engineer on shared platform capabilities and with Software Engineers and other consumers to define reliable data interfaces and products.Data Pipeline EngineeringDesign, build, and operate production-grade data pipelines for data extraction, ingestion, transformation, and loading (ETL/ELT)Integrate data from on-premises systems, enterprise applications, APIs, databases, SaaS platforms, files, streams, cloud services, and other operational data sourcesDevelop batch, incremental, change-data-capture (CDC), streaming, and event-driven ingestion patterns based on source-system and business requirementsBuild transformation pipelines that clean, enrich, standardise, join, aggregate, and structure raw data into trusted datasetsDesign secure and resilient mechanisms for transferring and synchronising data between on-premises, GCC, AWS, Azure, and other approved environmentsDesign pipelines for failure handling, retry, recovery, idempotency, scalability, and changing data volumesAutomate pipeline deployment, configuration, testing, and operationData Architecture & ModellingDesign and maintain cloud-native and hybrid data stores, data lakes, and analytical datasetsDevelop data models that provide consistent representations of enterprise, operational, and asset informationDefine schemas and data contracts between data producers and downstream consumersDesign data structures appropriate for operational applications, reporting, analytics, and machine-learning workloadsApply backwards-compatible schema changes and coordinate changes that may affect downstream consumersMaintain data lineage and metadata so datasets are traceable and discoverableWork with platform and application teams to define appropriate data-serving and integration patternsData Quality & ReliabilityImplement automated data validation, reconciliation, completeness, consistency, and quality controls throughout the pipeline lifecycleMonitor data freshness, pipeline health, processing latency, and data-quality indicatorsDetect and investigate ingestion failures, source-system changes, data-quality anomalies, and reconciliation differencesPrevent invalid or incomplete data from silently propagating to downstream consumersDefine appropriate SLOs for data freshness, availability, and pipeline reliabilityBuild monitoring, alerting, error handling, and recovery into data pipelines from the outsetAnalytics & Data ProductsBuild trusted datasets and reusable data products for applications, dashboards, operational reporting, and analyticsDevelop datasets supporting asset intelligence, operational visibility, capacity planning, trend analysis, and decision-makingEnable advanced analytics and machine-learning use cases using cloud-native data, analytics, and AI/ML capabilitiesWork with users and stakeholders to translate operational questions into appropriate datasets, metrics, and analytical productsSupport exploratory analysis and prototyping where required before operationalising successful approachesEnsure analytical outputs are based on governed, traceable, and reproducible dataData IntegrationDesign data architectures spanning on-premise infrastructure and cloud platformsIntegrate traditional enterprise systems with modern cloud-native data capabilitiesDesign for connectivity constraints, network boundaries, security zones, and data-residency requirementsImplement appropriate buffering, checkpointing, retry, and reconciliation where data crosses environment boundariesSelect appropriate integration patterns based on data volume, latency, source-system capability, and operational requirementsWork with infrastructure, network, security, and platform teams to establish secure data flowsSecurity & GovernanceEnsure data is collected, transmitted, stored, processed, and accessed according to applicable security requirementsEnforce appropriate access controls and least-privilege principles for data platforms and pipelinesEnsure sensitive information is appropriately classified and protected throughout the data lifecycleMaintain auditability and traceability of data-processing activitiesApply retention, archival, lifecycle, and deletion requirements to data productsParticipate in security, architecture, data-governance, and operational-readiness reviewsReliability & OperationsOperate and support production data pipelines and data productsParticipate in operational support and on-call responsibilities for owned servicesInvestigate production incidents and contribute to root-cause analysis and preventative improvementsMonitor pipeline performance, capacity, reliability, and costMaintain architecture documentation, data definitions, operational procedures, and runbooksContinuously improve pipeline automation, reliability, performance, and maintainabilityWhat are we looking for?Minimum 3–5 years of experience in data engineering, cloud data engineering, analytics engineering, software engineering, or a related disciplineAt least 2 years of hands-on experience designing, building, and operating production-grade data pipelinesDemonstrated experience with data extraction, ingestion, ETL/ELT, transformation, data modelling, and data qualityExperience using AWS and/or Azure native data capabilitiesExperience integrating data from APIs, databases, enterprise systems, files, or streaming sourcesExperience implementing batch, incremental, CDC, and/or event-driven data pipelinesExperience working with on-premises and/or cloud environments, with an understanding of hybrid integration patternsExperience applying software-engineering practices such as version control, automated testing, CI/CD, monitoring, and Infrastructure as Code to data solutionsExperience with Singapore Government platforms such as TechPass, SHIP-HATS, SEED, and GCCFamiliarity with OC/SN data-classification requirementsAWS or Azure cloud certificationsTreats data pipelines and data products as production software, not one-off scriptsKeeps pipeline code, schemas, infrastructure, and configuration under version controlUses automated testing, CI/CD, Infrastructure as Code, and monitoringDesigns pipelines for failure, retry, idempotency, scalability, and changing workloadsValidates data at ingestion and transformation boundariesEstablishes explicit data contracts between producers and consumersUnderstands when to use managed cloud-native capabilities rather than unnecessarily building and operating infrastructureConsiders downstream consumers before making schema or behavioural changesAutomates repeatable data-processing and operational activitiesBalances technical excellence with pragmatic delivery and operational sustainabilityAWS/Azure-native logging, streaming, storage, search and data servicesEnterprise servers, networks, applications, databases, virtualised infrastructure, and log sourcesPython, SQL, ETL/ELT, batch, incremental, CDC, streaming, and event-driven patternsRelational, dimensional, analytical, and domain-oriented data modellingValidation, reconciliation, quality monitoring, lineage, and anomaly detectionInfrastructure as Code Terraform / OpenTofuCI/CD GitLab CI/CD, SHIP-HATS or equivalent automated deployment practicesData preparation, analytical datasets, reporting, statistical analysis, and ML enablementWhat do we offer in return?Competitive Compensation: Market competitive salary and variable performance bonus aligned to your skills, impact, and contribution. Benefits: Outpatient medical, specialist medical coverage and generous customisable flexi benefits, or flexi allowance; life and health insurance, thoughtful perks like special occasions “red packet” and CNY goodies, etc. Employee Wellness: Support for your physical, mental, and overall well-being through year-round initiatives. Growth & Development: Learning programmes, certification support, and a dedicated staff development budget. (We are a “SHRI 2025 Gold winner” in “Learning & Development; Coaching & Mentoring”) Career Progression: Structured career pathways that enable you to grow along a technical/domain expert track or a leadership track. Competency Framework: A structured and practical framework to support you to develop, perform, and succeed. Flexible Work Arrangement: Staff may choose to work flexi-place, flexi-time, and flexi-load based on existing framework Why you'll love working with us? If you are looking for opportunities to collaborate with leading industry experts and be surrounded by highly motivated and talented peers, we welcome you to join us. We provide all employees with equal opportunities to grow and develop with us. We believe your success is our success. Does it sound like something you are interested in exploring further? Please be in touch with our team for an initial chat.Activate Interactive Singapore is an equal opportunity employer. Employment decisions will be based on merit, qualifications and abilities. Activate Interactive Pte Ltd does not discriminate in employment opportunities or practices on the basis of race, colour, religion, gender, sexuality, national origin, age, disability, marital status or any other characteristics protected by law. Protecting your privacy and the security of your data are longstanding top priorities for Activate Interactive Pte Ltd. Your personal data will be processed for the purposes of managing Activate Interactive Pte Ltd’s recruitment related activities, which include setting up and conducting interviews and tests for applicants, evaluating and assessing the results, and as is otherwise needed in the recruitment and hiring processes. Please consult our Privacy Notice (https://www.activate.sg/privacy-policy) to know more about how we collect, use, and transfer the personal data of our candidates. Here you can find how you can request for access, correction and/or withdrawal of your Personal Data.