Data Analyst

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November 7

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Incentive.me

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Artificial Intelligence • B2B • SaaS

Incentive. me is the leading AI sales technology company in Brazil that focuses on increasing sales and engaging sales teams through innovative incentive campaigns. Their solutions allow companies to easily create and manage incentive programs, automate variable remuneration, and offer attractive rewards, resulting in an average sales increase of 35% for their clients within six months. With over R$200 million distributed in rewards and a community of over 100,000 sales representatives, Incentive. me leverages artificial intelligence to enhance sales performance and team motivation.

51 - 200 employees

Founded 2017

🤖 Artificial Intelligence

🤝 B2B

☁️ SaaS

📋 Description

• Data Collection: Identify and collect relevant data from various sources such as databases, logs, data streams, APIs, and others. • Data Storage: Design and implement efficient, scalable data storage systems, which may include relational databases, NoSQL, data warehouses, and distributed storage systems. • Data Processing: Develop data processing pipelines to clean, transform, and prepare data for analysis. This may involve tools such as Apache Spark or other distributed processing solutions. • Data Integration: Ensure data integrity and consistency when integrating information from different sources. • Security and Privacy: Implement security measures and ensure compliance with data privacy regulations. • Data Analysis Support: Facilitate access to data for analysis through visualization tools, direct querying, or other data analysis methods. • Monitoring and Optimization: Monitor the performance of data systems, identify bottlenecks, and optimize performance as needed. • Team Collaboration: Work closely with data scientists, business analysts, and other professionals to understand and meet the organization’s data needs. • Documentation: Maintain clear and comprehensive documentation of data architectures, workflows, ETL (Extract, Transform, Load) processes, and other aspects related to data systems. • Troubleshooting: Identify and resolve data-related issues such as inconsistencies, processing failures, or performance problems. • Training and Knowledge Sharing: Collaborate with team members by sharing knowledge and providing training when necessary, especially to ensure data is used effectively across the organization. • Data Governance: Implement data governance practices to ensure data quality, consistency, and compliance, and establish policies for appropriate and ethical use of information. • Project Management: Participate in data projects from conception to implementation, ensuring deadlines are met and project objectives are achieved. • DevOps Collaboration: Work closely with development and operations teams to integrate DevOps practices into the data systems development lifecycle.

🎯 Requirements

• Languages: Python, advanced SQL. • Databases: Relational (MySQL, PostgreSQL), columnar (ClickHouse, BigQuery). • ETL and Modeling: Airflow, dbt Cloud / dbt CLI. • Big Data & Streaming: Apache Kafka, Apache Spark, Apache Flink (desirable). • Cloud & Infrastructure: Azure, Google Cloud, Kubernetes, Docker, Helm. • Version Control: Git. • Data Governance: Quality, metadata, and data lineage. • Analytical Skills: Problem-solving and process optimization. • Language: Intermediate English (desirable).

🏖️ Benefits

• Health insurance • Meal allowance • Transportation allowance • Home-office allowance • Dynamic work environment with opportunities for professional development