Chapter Lead Data Analytics | Personalization

Brazil·Campinaslead

AnalyticsData & AI

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Key Responsibilities

Management routine Manage and lead a high-performance team of Data Analysts and Analytics Engineers (8 to 10 resources). Work with product leaders, engineering,

Technical Tools

AnalyticsData & AI

Responsibilities

~1 min read

Manage and lead a high-performance team of Data Analysts and Analytics Engineers (8 to 10 resources).
Work with product leaders, engineering, and commercial strategy to form a unified data-driven strategy.
Support analysis request prioritization with stakeholders and Data Product Managers (DPMs).
Actively balance team leadership efforts with practical development/coding of data products, metrics, and visualizations to drive business.

Review to verify that best practices have been followed for high-quality products, recommend appropriate data sources and models, ensuring scalability and high reuse.
Drive the business strategy by providing insights into current performance and highlighting areas of opportunity for growth. To do this, conduct advanced data analysis, statistical modeling, and machine learning models to answer specific business questions, extract insights and predictive patterns from large datasets to explain and expose potential opportunities from the data.
Develop data sets/schemas consuming data from multiple sources such as internal databases, analysis tools, unstructured sources, and other external sources.
Demonstrate a solid understanding of complex data models, data structures, and best practices for data governance to support the data platform team in definitions and executions following best practices appropriate to use cases.

Bachelor’s degree completed in Information Systems, Data Science and Analytics, Mathematics, Statistics, Computer Engineering, or other data-related fields, with a strong foundation in Statistics.
Prior experience in technical management of Data Analyst or Analytics Engineering teams.
Advanced English is mandatory - will work with a global team.
Experience with B2B portfolio management would be a big plus.
Expertise in database query and reporting tools (SQL + Power BI + DAX).
Effective skills in programming languages (Python, PySpark, SQL).
Strong experience designing and maintaining CI/CD pipelines, using Git for code versioning, and actively participating in code review practices.
Strong experience with relational (SQL) and non-relational (NoSQL) database technologies.
Prior experience in cloud data solutions (e.g., Databricks, Redshift, BigQuery, Teradata, Snowflake) and cloud platforms such as AWS and Azure.
Experience in analyzing data to identify key insights, gaps, and inconsistencies.
Familiarity with the Systems Development Life Cycle and Agile Methodology.

Effectively communicate complex technical concepts and analytical insights to non-technical stakeholders and senior leadership.
Promote collaboration and a productive work environment by sharing knowledge and experience with direct subordinates.
Proven ability to seek unconventional solutions, explore opportunities, and develop innovative solutions.