{"id":2341357,"url":"https://alion.io/job/websparks-pte-ltd-data-engineer-public-sector","title":"Data Engineer (Public Sector)","company":{"id":252555,"name":"Websparks","domain":"websparks.sg","url":"https://alion.io/company/websparks","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"contractor","work_mode":"hybrid","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":{"min":7000,"max":9000,"currency":"SGD","period":"month","gross":true,"usd_annual":84432},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"CI/CD","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"GitLab","optional":false},{"name":"Linux","optional":false},{"name":"Polars","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Unix","optional":false}],"status":"live","first_seen_at":"2026-10-12T00:00:00Z","employer_posted_date":null,"last_verified_at":"2026-10-12T00:00:00Z","board_verified":false,"closed_at":null,"days_open":8,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":8},"description":"1-year contract, renewable\nGovernment project\nHybrid work arrangement\nRole Overview\nThe Data Engineer works closely with statisticians, analytical teams, and business stakeholders to design, build, and maintain the data infrastructure needed to support rigorous statistical production processes. The role centres on building reliable and maintainable data pipelines, validation and frameworks that support statistical production processes.\nYou will contribute to the migration and modernisation of legacy processes, ensuring that existing business logic is preserved and that outputs are accurately reconciled against current production results. You will also contribute to the engineering practices required to operate the platform reliably in production.\nKey Responsibilities\nDesign, develop and maintain efficient and reliable ETL processes and data pipelines for the ingestion, transformation, and integration of data from multiple source agencies.\nDevelop and maintain modular, production-quality code for statistical production processes, including optimising legacy processes while preserving business logic and reconciling outputs against existing results.\nDesign and maintain database schemas, data models and storage structures to support efficient ingestion, validation, transformation and retrieval of large datasets.\nBuild reusable data engineering components such as common libraries, configuration frameworks, logging standards, and utilities to streamline production workflows.\nImplement and maintain CI/CD pipelines for data engineering workflows, including automated testing and deployment, and establish workflows to safely isolate and synchronise Development, UAT, and Production environments.\nDesign and configure complex pipeline workflows and schedules using enterprise tools, including dependencies, failure handling, recovery and operational monitoring.\nEstablish version control structures using GitLab, set up code review frameworks, and produce technical documentation.\nMonitor and troubleshoot pipelines, perform root-case analysis and continuously improve operational reliability and system performance for large-scale datasets.\nCollaborate with technical team, business users and other stakeholders to translate business and statistical processing requirements into robust technical implementations.\nRequired Skills & Experience\n4-7 years of professional experience in data engineering, data platform development, or a related software engineering role.\nStrong proficiency in Python and SQL, including experience in complex data transformations, analysis, and quality monitoring.\nHands-on experience with dataframe processing libraries (e.g. Polars, pandas) for high-performance execution and memory-efficient processing of large datasets\nExperience with database management, data warehousing and developing ETL processes for data ingestion and integration\nExperience with version control using Git, including branching strategies, merge requests, code review, and CI/CD pipelines for automated testing and deployment\nWorking knowledge of Linux/Unix environments, shell scripting and command-line tools for data processing\nFamiliar with data governance policies, access control and security best practices.\nUnderstanding of software engineering practices such as modular design, configuration management, logging, exception handling, testing, and technical documentation.\nExperience with cloud technologies and orchestration/CI-CD tooling is an advantage\nExcellent problem-solving, analytical, and communication skills, with the ability to work independently in an agile team environment\n/Ref: T24-266\nSkills\nValidation, Code Review, UAT, Design, Business Process Re-engineering, Pipeline Management, Data Pipeline, Root Cause Analysis, Dataframe, Transformation, Library Management, integrate Data sources, Deployment Automation, Workflow Solutions, Maintain Database Schemas, Failure Analysis, Identify dependencies","description_format":"text","description_chars":3948,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Government","Web Development Services","Digital Marketing"],"lifecycle":[{"event":"open","at":"2026-10-12T10:36:58Z"}],"visa":[],"liveness":{"score":54,"band":"ok","label":"Likely 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