{"id":1151325,"url":"https://alion.io/job/careersgov-data-engineer-integrated-e-services-ite-headquarters-2-yr-cr-2","title":"Data Engineer - Integrated E-Services [ITE Headquarters] – 2 Yr Cr","company":{"id":178377,"name":"Careers@Gov","domain":"careers.gov.sg","url":"https://alion.io/company/careersgov","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":true,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":93,"open_postings":257,"ghost_share":0,"stale_share":0.237,"repost_share":0.066,"time_to_fill_p50_days":28,"computed_at":"2026-10-24T06:02:35Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":45000,"max_usd":108000,"period":"year","method":"role_country_seniority_unknown","sample_n":97},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Azure DevOps","optional":false},{"name":"Azure SQL Database","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-22T00:00:00Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-24T22:49:41Z","board_verified":true,"closed_at":null,"days_open":33,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":33},"description":"[What the role is]\nThe Data Engineer will support the design, development, and maintenance of reliable data platforms, pipelines, and analytics-ready datasets. This role is suited for a junior to middle experience level candidate who is keen to build practical data engineering capabilities using modern cloud data platforms such as Microsoft Fabric, Azure data services, and medallion architecture patterns.[What you will be working on]\nYou will help design, build, and maintain data solutions that support reporting, analytics and daily operations within the organisation:\nCollaborate with stakeholders to understand business requirements, user needs and data-related issues.\nDesign, build, and maintain data pipelines, data models, and structured datasets to support reporting, analytics and decision-making.\nOrganise and manage data across defined layers, from raw source data to cleansed, transformed and business-ready datasets.\nEnsure data quality through validation, documentation, lineage tracking, access management and operational monitoring.\nMonitor data pipeline performance, investigate failures or anomalies and document remediation actions to ensure reliable data delivery.\nSupport the implementation and enhancement of cloud-based data solutions while ensuring compliance with security, audit, governance and government ICT requirements.\nContribute to ITE’s enterprise data capability-building by supporting governed, reliable and reusable data assets for reporting, analytics, data sharing and future AI-enabled use cases.\n[What we are looking for]\nEssential requirements\nRelevant qualification in Computer Science, Information Systems, Data Engineering, Data Analytics, Software Engineering or a related discipline.\nUnderstanding of ETL or ELT concepts, data pipelines, data warehousing, lakehouse architecture or analytics platform support.\nGood foundation in SQL and data modelling concepts.\nWorking knowledge of at least one scripting or data processing language such as Python, PySpark or similar.\nAbility to work with structured and semi-structured data from multiple source systems.\nGood analytical, troubleshooting, documentation and communication skills.\nAbility to work with stakeholders to clarify requirements and translate data needs into technical implementation tasks.\nAdvantageous requirements\nHands-on exposure to Microsoft Fabric components such as Lakehouse, Warehouse, Data Factory, Notebooks, Dataflows, Semantic Models, OneLake and Power BI integration.\nExposure to Azure Data Lake, Azure Data Factory, Azure Databricks, Azure SQL, Azure DevOps or similar cloud data platforms.\nUnderstanding of medallion architecture, including Bronze, Silver and Gold layers.\nExperience in data quality checks, reconciliation, monitoring, lineage tracking and operational support of data pipelines.\nFamiliarity with Git, CI/CD, deployment practices and environment management.\nAwareness of cloud security, access control, data protection, audit requirements, Government on Commercial Cloud and IM8 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