{"id":3075094,"url":"https://alion.io/job/agoro-carbon-alliance-senior-analytics-engineer","title":"Senior Analytics Engineer","company":{"id":1877326,"name":"Agoro Carbon Alliance","domain":"agorocarbonalliance.com","url":"https://alion.io/company/agorocarbonalliance","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"BambooHR","truth_index":null},"role":"Analytics","role_family":"Analytics","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["São Paulo, Brazil"],"countries":["BR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":35000,"max_usd":104000,"period":"year","method":"role_seniority_country_cell","sample_n":13},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ETL/ELT","optional":false},{"name":"Metabase","optional":false},{"name":"SQL","optional":false},{"name":"Airflow","optional":true},{"name":"Amazon Redshift","optional":true},{"name":"Amazon S3","optional":true},{"name":"AWS","optional":true},{"name":"AWS Lambda","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Python","optional":true}],"status":"live","first_seen_at":"2026-10-21T00:00:00Z","employer_posted_date":"2026-10-21","last_verified_at":"2026-11-01T00:21:11Z","board_verified":true,"closed_at":null,"days_open":11,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":11},"description":"About the Role\nWe are seeking a Senior Analytics Engineer to design, build, and maintain the data pipelines, analytical models, and trusted datasets that support business operations, reporting, and decision-making.\nThis is a hands-on technical role that combines data engineering, analytics engineering, and business problem-solving. You will work across operational databases, data warehouses, and reporting systems to transform complex data into reliable, reusable information.\nWorking closely with business stakeholders, software engineers, and data teams, you will help define business metrics, establish consistent data definitions, improve data quality, and reduce reliance on manual reporting processes.\nThe ideal candidate understands not only how to move and transform data, but also how to evaluate where data should reside, how it should be modeled, and how its accuracy and reliability can be maintained.\nYou will be expected to independently investigate complex data challenges, challenge unclear requirements, and recommend sustainable solutions that support both current operational needs and future growth.\nKey Responsibilities\nData Engineering & Analytics Development\nDesign, develop, and maintain scalable data pipelines for ingestion, transformation, and delivery. \nBuild reusable analytical datasets and data models that support multiple business processes and reporting needs.\nDevelop, optimize, and maintain SQL transformations, business logic, and analytical queries. \nEvaluate data integration approaches across operational systems, databases, data warehouses, and reporting platforms. \nDesign and maintain pipeline orchestration, scheduling, dependencies, and failure recovery processes. \nApply appropriate data modeling and transformation practices to improve maintainability, performance, and reuse. \nData Quality, Reliability & Governance \nDevelop validation, reconciliation, and monitoring processes to ensure data completeness, consistency, and accuracy. \nInvestigate and resolve data quality issues, pipeline failures, and discrepancies between systems. \nEstablish and maintain trusted business metrics, standardized definitions, and documented transformation logic. \nImprove data traceability, auditability, and reproducibility across analytical processes. \nIdentify opportunities to improve data freshness, pipeline performance, and operational reliability. \nSupport appropriate data access controls, security practices, and governance standards. \nBusiness Analytics & Collaboration\nWork directly with business stakeholders to understand reporting needs, business processes, and analytical requirements. \nClarify and challenge conflicting definitions, assumptions, business rules, and data requirements before implementation. \nDevelop and maintain datasets that support dashboards, reports, and analytical tools such as Metabase.Collaborate with software engineering and other technical teams to improve data integration and source-system reliability. \n\nIdentify opportunities to replace recurring manual reports and data requests with automated, reusable solutions. \nCommunicate technical findings, data limitations, and recommended approaches clearly to technical and non-technical stakeholders. \nEngineering Practices & Continuous Improvement\nApply version control, code reviews, testing, and documentation standards to data engineering work. \nContribute to data architecture discussions and technical design decisions. \nImprove pipeline maintainability, query performance, and operational support processes. \nHelp establish repeatable engineering practices that support reliable and scalable analytics. \nShare technical knowledge and contribute to continuous improvement across the team. \nRequired Qualifications\n5+ years of professional experience in analytics engineering, data engineering, business intelligence engineering, or a closely related discipline. \nAdvanced SQL proficiency, including complex joins, common table expressions, window functions, aggregations, and query optimization. \nStrong understanding of relational databases, analytical data warehouses, and data modeling principles. \nExperience designing, developing, or maintaining ETL/ELT pipelines. \nExperience building reusable analytical datasets and implementing complex business transformations. \nUnderstanding of data ingestion, orchestration, scheduling, dependencies, error handling, and data delivery patterns. \nApply version control, code reviews, testing, and documentation standards to data engineering work. \nContribute to data architecture discussions and technical design decisions. \nImprove pipeline maintainability, query performance, and operational support processes. \nHelp establish repeatable engineering practices that support reliable and scalable analytics. \nShare technical knowledge and contribute to continuous improvement across the team.\nPreferred Qualifications\nExperience with Amazon Redshift and PostgreSQL, including AWS RDS. \nExperience with Apache Airflow or comparable orchestration platforms. \nHands-on experience with AWS data services such as S3, Lambda, Glue, or Database Migration Service (DMS). \nProficiency in Python for data processing, automation, or pipeline development. \nExperience with Metabase or comparable business intelligence platforms. \nExperience implementing automated data quality checks, source-to-target reconciliation, and pipeline monitoring. \nFamiliarity with data governance, lineage, metadata management, auditability, and access control. \nExperience with geospatial, agricultural, scientific, or other complex operational datasets. \nExperience supporting analytical environments where accuracy, reproducibility, and traceability are critical. \nWhat success looks like this role\nDeliver trusted, reusable analytical datasets that support business reporting and decision-making.\nImprove consistency and accuracy across data originating from multiple operational systems.\nReduce manual reporting effort through reliable, automated data pipelines.\nEstablish clear business definitions and maintainable transformation logic.\nImprove data pipeline reliability, performance, monitoring, and recovery.\nStrengthen collaboration between business stakeholders, software engineering, and data teams.\nContribute to a scalable and well-documented data foundation that supports future business growth.","description_format":"text","description_chars":6358,"description_truncated":false,"requirements":{"experience_years_min":5,"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":["AgTech","ESG & Carbon Accounting Software"],"lifecycle":[{"event":"open","at":"2026-10-22T10:35:52Z"}],"visa":[],"liveness":{"score":76,"band":"hot","label":"Hiring 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