Senior Analytics Engineer

Job not on LinkedIn

🔥 0 minutes ago

🇧🇷 Brazil – Remote

⏰ Full Time

🟠 Senior

📊 Analytics Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Agoro Carbon Alliance

WebsiteLinkedInAll Job Openings

51 - 200 employees

🌾 Agriculture

🌍 Social Impact

🔬 Science

Agriculture • Social Impact • Science

Agoro Carbon Alliance is an organization that collaborates with farmers, ranchers, agronomists, and businesses to facilitate the generation of carbon credits through sustainable agricultural practices. Their approach focuses on carbon sequestration in soil, utilizing nature-based solutions that offer economic value and contribute to reducing greenhouse gas emissions. With expert support and certification processes, Agoro Carbon ensures the high quality of the carbon credits produced, connecting them with businesses aiming to meet climate-emission goals. As part of Yara International, Agoro Carbon draws on extensive agronomic expertise to improve soil health, foster biodiversity, and promote sustainable food systems globally.

📋 Description

• Design, develop, and maintain scalable data pipelines for ingestion, transformation, and delivery • Build reusable analytical datasets and data models supporting business processes and reporting • Develop, optimize, and maintain SQL transformations, business logic, and analytical queries • Evaluate data integration approaches across operational systems, databases, data warehouses, and reporting platforms • Design and maintain pipeline orchestration, scheduling, dependencies, and failure recovery processes • Apply data modeling and transformation practices to improve maintainability, performance, and reuse • Develop validation, reconciliation, and monitoring processes for data completeness, consistency, and accuracy • Investigate and resolve data quality issues, pipeline failures, and cross-system discrepancies • Establish trusted business metrics, standardized definitions, and documented transformation logic • Improve data traceability, auditability, reproducibility, freshness, performance, and operational reliability • Support appropriate data access controls, security practices, and governance standards • Work with business stakeholders to understand reporting needs, processes, and analytical requirements • Clarify and challenge conflicting definitions, assumptions, business rules, and data requirements • Develop and maintain datasets supporting dashboards, reports, and analytical tools such as Metabase • Collaborate with software engineering and technical teams to improve data integration and source-system reliability • Replace recurring manual reports and data requests with automated, reusable solutions • Communicate technical findings, data limitations, and recommended approaches to technical and non-technical stakeholders • Apply version control, code reviews, testing, and documentation standards • Contribute to data architecture discussions and technical design decisions • Improve pipeline maintainability, query performance, and operational support processes • Share technical knowledge and contribute to continuous improvement across the team

🎯 Requirements

• 5+ years of professional experience in analytics engineering, data engineering, business intelligence engineering, or a closely related discipline • Advanced SQL proficiency, including complex joins, common table expressions, window functions, aggregations, and query optimization • Strong understanding of relational databases, analytical data warehouses, and data modeling principles • Experience designing, developing, or maintaining ETL/ELT pipelines • Experience building reusable analytical datasets and implementing complex business transformations • Understanding of data ingestion, orchestration, scheduling, dependencies, error handling, and data delivery patterns • Apply version control, code reviews, testing, and documentation standards to data engineering work • Contribute to data architecture discussions and technical design decisions • Improve pipeline maintainability, query performance, and operational support processes • Help establish repeatable engineering practices that support reliable and scalable analytics • Share technical knowledge and contribute to continuous improvement across the team • Preferred: Experience with Amazon Redshift and PostgreSQL, including AWS RDS • Preferred: Experience with Apache Airflow or comparable orchestration platforms • Preferred: Hands-on experience with AWS data services such as S3, Lambda, Glue, or Database Migration Service (DMS) • Preferred: Proficiency in Python for data processing, automation, or pipeline development • Preferred: Experience with Metabase or comparable business intelligence platforms • Preferred: Experience implementing automated data quality checks, source-to-target reconciliation, and pipeline monitoring • Preferred: Familiarity with data governance, lineage, metadata management, auditability, and access control • Preferred: Experience with geospatial, agricultural, scientific, or other complex operational datasets • Preferred: Experience supporting analytical environments where accuracy, reproducibility, and traceability are critical

🏖️ Benefits

• Remote work arrangement