Analytics Engineer

Accountabilities: Perform business and data analysis to support internal initiatives and external or client-driven requests. Investigate data issues, bugs, inconsistencies, and quality problems, identifying root causes and coordinating with relevant teams to drive resolution. Proactively monitor data models and services to identify potential quality, accuracy, consistency, or reliability issues. Validate business rules, KPIs, data transformations, and analytical outputs to ensure they accurately reflect business requirements. Contribute to the development, maintenance, and validation of data models and services used across the organization. Review and maintain accurate, clear, and up-to-date documentation covering data models, business rules, metrics, processes, and services. Support data governance and standardization initiatives, helping establish consistent definitions, structures, naming conventions, and quality standards. Use advanced SQL and analytical techniques to investigate datasets, validate information, and produce well-supported conclusions. Leverage AI tools to accelerate data analysis, SQL development, documentation, and day-to-day analytical workflows. Collaborate with Analytics, Engineering, Product, and other cross-functional teams to translate business needs into reliable data solutions. Requirements Advanced SQL proficiency, including complex queries, CTEs, window functions, aggregations, joins, and data validation techniques. Strong understanding of data modeling, data structures, and data quality principles. Experience using Claude or comparable AI tools to support data analysis, SQL development, documentation, and productivity. Good knowledge of Excel, including formulas, lookups, pivot tables, data analysis, and data validation. Basic knowledge of Databricks, including notebooks, tables, catalogs, and SQL querying. Strong problem-solving and analytical skills, with the ability to investigate issues, identify root causes, evaluate inconsistencies, and develop effective solutions. Exceptional attention to detail, particularly when working with data accuracy, consistency, and validation. Experience with e-commerce data and KPIs such as sales, revenue, orders, conversion rate, ROAS, ACOS, TACOS, CPC, and related commerce or advertising metrics is a plus. Familiarity with data from platforms such as Amazon, Walmart, Shopify, Google Ads, Meta, or similar ecosystems is advantageous. Experience with data governance, quality monitoring, documentation, and standardization practices is desirable. Experience working with large and complex datasets is a plus. Ability to collaborate effectively with Analytics, Engineering, Product, and other cross-functional teams. Strong written and verbal communication skills and the ability to translate business requirements into clear data solutions. Benefits 100% remote work from Brazil. PJ contractor model , offering flexibility within a remote working environment. Opportunity to work with scalable data models and governance practices supporting business-critical analytics. Exposure to modern data technologies, including Databricks and advanced SQL workflows. Opportunity to use AI-powered tools to enhance data analysis, development, documentation, and productivity. Collaboration with multidisciplinary teams across Analytics, Engineering, Product, and other business functions. Opportunity to contribute to data quality, governance, standardization, and continuous improvement initiatives. Exposure to e-commerce, retail media, advertising, and complex commercial datasets. Professional growth within a technology-driven and data-focused environment.