Senior Data Analyst

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2 days ago

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Informação que transforma você, a justiça e o mundo.

201 - 500 employees

📋 Description

• Strategic Analysis: Lead complex analytics projects end-to-end, from problem definition and data collection to presenting insights and recommendations to leadership. • Data Visualization and Storytelling: Develop interactive dashboards and clear reports (using tools such as Metabase, Looker, etc.) to communicate findings effectively to both technical and non-technical stakeholders. • Modeling and Hypothesis Testing: Apply statistical and modeling methods to perform predictive analyses, A/B tests, and identify trends and growth opportunities. • Data Extraction and API Integration: Design, develop, and maintain scripts (primarily in Python) to extract data from partner service APIs and third-party platforms. • Data Warehouse Enrichment: Collaborate with the data engineering team to integrate new data sources into our environment, ensuring data quality, consistency, and availability. • Mentorship: Serve as a technical reference for other analysts on the team, sharing knowledge and promoting best practices in analysis and data handling.

🎯 Requirements

• Proven experience as a Data Analyst, with a portfolio demonstrating the ability to drive business impact through analysis. • Advanced proficiency in SQL for complex queries across relational and non-relational databases. • Proven experience with Business Intelligence and Data Visualization tools. • Strong programming skills in Python, specifically for data manipulation (Pandas, NumPy) and API consumption. • Hands-on experience extracting and automating data collection from REST/GraphQL APIs, including authentication processes (OAuth, API Keys, etc.). • Ability to communicate complex insights simply and directly to diverse audiences. • Proactive, curious profile with excellent problem-solving skills.

🏖️ Benefits

• Strategic Analysis: Lead complex analytics projects end-to-end, from problem definition and data collection to presenting insights and recommendations to leadership. • Data Visualization and Storytelling: Develop interactive dashboards and clear reports (using tools such as Metabase, Looker, etc.) to communicate findings effectively to both technical and non-technical stakeholders. • Modeling and Hypothesis Testing: Apply statistical and modeling methods to perform predictive analyses, A/B tests, and identify trends and growth opportunities. • Data Extraction and API Integration: Design, develop, and maintain scripts (primarily in Python) to extract data from partner service APIs and third-party platforms. • Data Warehouse Enrichment: Collaborate with the data engineering team to integrate new data sources into our environment, ensuring data quality, consistency, and availability. • Mentorship: Serve as a technical reference for other analysts on the team, sharing knowledge and promoting best practices in analysis and data handling.