{"id":2604535,"url":"https://alion.io/job/proactiviti-senior-analytics-engineer","title":"Senior Analytics Engineer","company":{"id":4423600,"name":"Proactiviti","domain":"proactiviti.com","url":"https://alion.io/company/proactiviti","size_band":null,"is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":"Manatal","truth_index":null},"role":"Analytics","role_family":"Analytics","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"Data Vault","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Looker","optional":false},{"name":"MySQL","optional":false},{"name":"Pentaho","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Power BI","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"Agile","optional":true},{"name":"AWS","optional":true},{"name":"GCP","optional":true}],"status":"live","first_seen_at":"2026-10-15T09:17:07Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-15T16:26:18Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"We are looking for an experienced Senior Analytics Engineer based in Latin America to lead full-cycle data-warehouse and analytics platform implementations for our global clients. This role requires a strong mix of technical expertise, business acumen, and communication skills, as you will work directly with stakeholders across North America, Europe, and Asia.\nYou will own the entire analytics engineering lifecycle from requirements gathering and data modeling to building ETL/ELT pipelines and delivering high-quality reporting and analytics solutions.\nKey Responsibilities:\nData Architecture & Modeling\nLead end-to-end data-warehouse implementations, including requirements discovery, solution design, development, and deployment.\nBuild and maintain scalable data models (conceptual, logical, and physical) following industry best practices (e.g., Kimball, Data Vault).\nTranslate business needs into clear technical specifications, documentation, and data requirements.\nEstablish and enforce data architecture standards, schemas, and naming conventions.\nETL/ELT Pipeline Development\nDesign, develop, and optimize automated ETL/ELT workflows using tools such as Pentaho, TimeXtender, DBT, Azure Data Factory, or similar.\nCreate transformation logic, data-quality validation, and workflow orchestration for complex integrations.\nImplement robust monitoring, quality checks, and performance optimization across all pipelines.\nEnsure data accuracy, consistency, and reliability across source and target systems.\nAnalytics & Reporting Enablement\nDeliver analytics-ready datasets for BI platforms such as Power BI, Tableau, Looker, or Qlik.\nCollaborate closely with data analysts, BI developers, and business teams to enable advanced reporting and insights.\nOptimize data structures for performance, usability, and scalability within reporting environments.\nClient Collaboration & Leadership\nAct as a technical lead for international client engagements across multiple time zones.\nLead requirements workshops, solution walkthroughs, and technical presentations with senior stakeholders.\nCollaborate with global engineering, analytics, and consulting teams.\nMentor junior engineers and contribute to best-practice development across the organization.\nRequired Qualifications:\n5+ years of experience as an Analytics Engineer, Data Engineer, or Data Warehouse Engineer.\nProven experience owning end-to-end data-warehouse implementations.\nStrong hands-on experience with ETL/ELT tools: Pentaho, TimeXtender, DBT, Azure Data Factory, or similar platforms.\nAdvanced proficiency in SQL and experience with modern cloud data warehouses (SQL Server, Snowflake, BigQuery, Redshift, Azure Synapse, MySQL, PostgreSQL).\nExpert understanding of data modeling principles and dimensional modeling frameworks.\nExperience documenting business requirements, technical specifications, data mappings, and process flows.Familiarity with Git-based version control and CI/CD for data pipelines.\n\nEnglish proficiency at C1 level (Business Proficient) - capable of leading client meetings, presenting solutions, and writing technical documentation in 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