{"id":2084335,"url":"https://alion.io/job/ul-solutions-data-engineer","title":"Data Engineer","company":{"id":1754684,"name":"UL Solutions","domain":"ul.com","url":"https://alion.io/company/ul-com","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":88,"open_postings":52,"ghost_share":0,"stale_share":0.269,"repost_share":0,"time_to_fill_p50_days":62,"computed_at":"2026-10-10T05:45:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Makati, 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data to understand structure, quality, business meaning, and transformation requirements.\nDesign, develop, test, and maintain data pipelines that ingest, transform, and deliver data from internal and external sources.\nBuild scalable ETL/ELT solutions across cloud data platforms, data warehouses, lakehouse patterns, and data integration tools.\nDevelop and optimize SQL, stored procedures, scripts, and reusable data engineering components.\nImplement data quality checks, reconciliation controls, error handling, logging, lineage capture, and pipeline monitoring.\nApply automated testing, version control, code review, continuous integration, and deployment practices.\nMonitor pipeline execution, investigate failures, resolve data issues, and support root cause analysis.\nCollaborate with business users, data owners, data stewards, architects, security teams, and platform engineers.\nDocument technical designs, mappings, transformation logic, operational procedures, dependencies, and support information.\nRead and follow the Underwriters Laboratories Code of Conduct and all physical and digital security practices.\n Education & Experience\nBachelor’s degree in Computer Science, Information Systems, Engineering, Data Analytics, Mathematics, or a related discipline, or equivalent combination of education and experience.\n3+ years of experience designing, developing, testing, and supporting data pipelines, ETL/ELT processes, integrations, or analytics data solutions, preferably within a modern cloud-based data lakehouse environment.\nTechnical Skills\nStrong SQL expertise, including query development, transformation logic, troubleshooting, optimization, and performance tuning.\nProficiency in Python development for data engineering and analytics solutions.\nExperience building and maintaining scalable ETL/ELT data pipelines on modern data platforms.\nHands-on experience with cloud data technologies and platforms such as Microsoft Azure, Snowflake, SQL Server, or similar solutions.\nSolid understanding of dimensional data modeling methodologies (Kimball), curated datasets, semantic layers, and analytics-ready data products.\nKnowledge of data profiling, data quality, validation, and management of structured, semi-structured, and unstructured data.\nExperience utilizing Git-based version control, code reviews, automated testing, CI/CD pipelines, and Agile delivery practices.\nUnderstanding of secure data handling, governance, lineage, privacy, and access control principles.\nProfessional Skills\nStrong analytical thinking, problem-solving, and root-cause analysis capabilities.\nAbility to collaborate effectively with both business stakeholders and technical teams.\nExcellent communication skills, with the ability to translate technical concepts into business value.\nInquisitive mindset, strong attention to detail, and commitment to delivering high-quality solutions.\nContinuous learning mindset with a willingness to adopt new technologies, 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