{"id":2312859,"url":"https://alion.io/job/futureproof-data-engineer-aws-dbt-trinodatabricks","title":"Data Engineer (AWS, DBT, Trino/Databricks)","company":{"id":1940064,"name":"Futureproof","domain":"runfutureproof.com","url":"https://alion.io/company/runfutureproof","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"contractor","work_mode":"remote","remote_scope":"stated_regions","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["DE","FR","GB","AT","BE","BG","HR","CY","CZ","DK","FI","HU","IE","IT","NL","NO","PL","RO","ES","SE","CH","EE","GR","IS","LV","LI","LT","LU","MT","PT","SK","SI"],"hiring_countries_total":32,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Git","optional":false},{"name":"Presto","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"SQL","optional":false},{"name":"Trino","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-11T23:48:19Z","employer_posted_date":null,"last_verified_at":"2026-10-11T23:48:19Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"This is a remote position.We are looking for an experiencedData Engineerto support the migration and integration of data from multiple enterprise and laboratory systems. The project is primarily focused ondbt, advanced SQL, and data modellingrather than Databricks or large-scale PySpark processing. \nThe successful candidate will design new data models, develop complex transformations, and consolidate data from several source databases into a unified AWS-based data platform.\nKey Responsibilities\nDesign logical and physicaldata modelsbased on technical and business requirements.\n\nDevelop, test, and maintain complex data transformations usingdbt and SQL.\n\nMigrate and consolidate data from multiple databases and source systems.\n\nUseTrino/Prestoto query, join, and transform data distributed across different sources.\n\nIntegrate data from enterprise and laboratory systems such asSAP, GLIMS, and Veeva.\n\nBuild reusable, maintainable, and well-documented transformation models.\n\nValidate migrated data and investigate data-quality or consistency issues.\n\nOptimize complex SQL queries and transformation processes.\n\nSupport data lineage, traceability, integrity, and documentation.\n\nWork with data stored or processed within AWS, particularlyAmazon S3 and Athena.\n\nParticipate in Agile delivery, code reviews, testing, and CI/CD activities.\n\nCollaborate with data architects, analysts, engineers, and pharmaceutical business stakeholders.\n\nDevelop new solutions rather than only maintaining existing pipelines.\n\nRequirements\nStrong hands-on experience withdbt. \n\nAdvanced proficiency inSQL, including:\nComplex joins and transformations \n\nCTEs and window functions \n\nQuery optimization \n\nData reconciliation and validation \n\nPractical experience withdata modelling, including the ability to design a model from business or technical requirements. \n\nExperience migrating and consolidating data from multiple databases. \n\nExperience with distributed query engines such as:\nTrino\n\nPresto\n\nWorking knowledge of AWS data services, particularly:\nAmazon S3 \n\nAmazon Athena \n\nAWS Glue \n\nExperience building reliable, production-ready data transformation pipelines. \n\nUnderstanding of relational databases and data warehousing concepts. \n\nAdditional Relevant Skills\nPython, Scala, or PySpark for scripting, automation, or supplementary data transformation.\n\nExperience withPostgreSQLor another relational target database.\n\nFamiliarity with Git and CI/CD deployment pipelines.\n\nExperience working in an Agile delivery environment.\n\nKnowledge of data quality, lineage, governance, and integrity principles.\n\nDomain ExperienceExperience integrating data from any of the following is valuable:\n\nSAP ERP\n\nGLIMS or other LIMS platforms\n\nVeeva\n\nPharmaceutical manufacturing or laboratory systems\n\nExperience withGxP regulations and pharmaceutical data-integrity requirementsis preferred but not necessarily essential.\nQualificationsCandidates should meet one of the following:\n\nBachelor’s degree in Computer Science, Information Technology, Engineering, or a related discipline, with at least4 years of relevant technical experience; or\n\nAt least8 years of equivalent experiencein data engineering, data modelling, data integration, or cloud analytics without a degree.\n\nIdeal CandidateThe ideal candidate is a SQL-focused Data Engineer with strong practical experience indbt and data modelling. They should be comfortable combining data from several databases, designing new data structures, and implementing complex transformations with Trino/Presto in an AWS environment.\n\nBenefits\n\nLocation:European Union\n\nContract Type:Freelance / Contract\n\nStart date:Summer, 2026\n\nTime Allocation:40 hours/week \n\nGlobal Pharmaceutical Company in Prague \n\nOriginally posted on Himalayas","description_format":"text","description_chars":3762,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Germany","iso":"DE","kind":"region"},{"name":"France","iso":"FR","kind":"region"},{"name":"United 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