{"id":2595220,"url":"https://alion.io/job/auxis-data-engineer-associate","title":"Data Engineer Associate","company":{"id":2615260,"name":"Auxis","domain":"auxis.com","url":"https://alion.io/company/auxis","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"iCIMS","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bogotá, Colombia"],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":1,"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":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-15T07:00:54Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-15T11:13:52Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Job Summary\nData & Analytics function is dedicated to designing and delivering robust global data platforms that enable data ops, business solutions and high-quality analytics. The Data Engineer (Associate) designs, builds, and maintains data pipelines and analytics-ready datasets that power reporting, advanced analytics, and data products. This role focuses on implementing well-defined ingestion and transformation patterns, ensuring data quality and reliability, and collaborating closely with analytics, data science, and business stakeholders to deliver trusted data assets.\nResponsibilities\nDesign, build, and maintain batch and/or streaming data pipelines and contribute to the development of reusable data pipeline components, templates and utilities using established engineering standards, patterns, and reference architectures.\nAssist with onboarding new data sources by performing source data profiling, documenting assumptions, and validating data completeness and quality.\n Implement data transformations and analytical models to produce curated, analytics-ready datasets that support reporting and advanced analytics use cases.\n Support schema evolution and change management to minimize downstream impact when source data changes.\n Collaborate with data analysts, data architects, and product teams to understand data requirements and translate them into well-defined technical solutions.\nApply data quality checks, validation rules, and monitoring; support the investigation and resolution of data issues and defects.\nSupport optimization efforts by identifying inefficient queries or unnecessary data processing patterns.\nCreate and maintain clear documentation for pipelines, data models, and business logic to support transparency, reuse, and operational support.\n Participate in code reviews, testing, and CI/CD processes to ensure engineering quality and consistency.\nSupport production operations, including incident triage, root cause analysis, and corrective actions, in partnership with Data Ops.\n Assist in maintaining dashboards or alerts that surface data reliability issues before they impact consumers.\nAdhere to governance-by-design principles, implementation of data security and privacy controls, including role-based access, encryption standards, and data classification.\nSupport the implementation of metadata management practices, including dataset descriptions, data lineage, and ownership information.\nExecute unit and integration tests for data pipelines to validate transformations, business rules, and expected outputs.\n Participate in sprint planning and backlog refinement, providing input on effort, dependencies, and technical considerations.\nSkills and Experience\nSkills & Capabilities\nEnglish level B2+\nProficiency in SQL and at least one programming language, such as Python.\nWorking knowledge of cloud-native data services and concepts such as storage layers, compute separation, and cost-aware design.\nExperience integrating from diverse sources including APIs, CSV, JSON, XML, Dataverse and different databases into centralized data platforms.\nSolid understanding of ETL / ELT concepts, data modeling techniques (dimensional and analytical models), and the data lifecycle.\nFamiliarity with modern data platforms (Snowflake or MS Fabric), including data warehouse, data lake, or lakehouse architectures.\n Exposure to semantic layers or analytics consumption patterns (e.g., BI tools, metrics definitions).\n Experience with version control and foundational CI/CD practices.\nStrong analytical thinking, problem-solving, and collaboration skills.\nAbility to learn quickly and contribute effectively within a team-oriented, Agile delivery environment.\nAwareness of data privacy regulations and secure data handling practices in enterprise environments.\n Strong written communication skills for documenting technical decisions and explaining data concepts to non-technical stakeholders.\nEducation / Professional Experience/ Qualifications\nBachelor's degree in Computer Science, Engineering, Information Systems, Analytics, or equivalent practical experience.\n1-3 years of relevant experience in data engineering, analytics engineering, or related technical 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now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":17,"reasons":["conf:2","win:early","comp:junior"],"computed_at":"2026-10-15T13:57:13Z"},"pay":null,"html_url":"https://alion.io/job/auxis-data-engineer-associate","json_url":"https://alion.io/job/auxis-data-engineer-associate.json","meta":{"generated_at":"2026-10-15T13:57:13Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per 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