Staff Analytics Engineer

Staff Analytics Engineer

The Staff Analytics Engineer is responsible for acting strategically and technically in transforming data into valuable business insights. Core responsibilities include:

• Developing and maintaining efficient, scalable data pipelines, ensuring data quality, integrity, and availability for analysis and decision-making.
• Collaborating with the data architecture team to design and implement analytics solutions, aligning both technical and business requirements.
• Supporting the continuous development and evolution of the analytics and machine learning platform, contributing to the integration of new technologies and best practices.
• Leading technical initiatives in analytics projects, serving as a reference in resolving technical challenges and supporting the team throughout the entire project lifecycle.
• Actively participating in discussions about the evolution of the data area, proposing new approaches, tools, and projects focused on innovation and solving the problems of internal clients.
• Ensuring the implementation of DataOps and CI/CD practices, optimizing the development, testing, and operation of data flows.
• The ideal profile for the position includes analytical thinking, proactivity, a results-driven mindset, and excellent communication skills to translate business needs into robust and scalable technical solutions.

This is a remote position.

Required Technical Skills:

• Expertise in SQL for large-scale data manipulation and analysis.
• Proficiency in Python, focused on automation of pipelines, data analysis, and API integration.
• Advanced experience with Databricks, including notebooks, Delta Lake, and integration with various data sources.
• Solid knowledge of AWS, especially the following services:
• Glue (serverless ETL)
• Athena (serverless SQL queries)
• S3 (data storage)
• Lambda (serverless function execution)
• Practical knowledge of Terraform for provisioning and managing infrastructure as code (IaC).
• Experience with Git for code versioning and team collaboration.
• Knowledge in BI and data modeling, with the ability to structure data for visualizations and strategic analyses.
• Experience with data orchestration (e.g., Airflow).
• Experience working in environments with high data volume and performance requirements.
• Experience with modern data architecture (Data Lakehouse, medallion architecture).

Differentials:

• Familiarity with Machine Learning and Artificial Intelligence tools, such as:
• AWS Bedrock (generative and foundational models)
• AWS SageMaker (creation, training, and deployment of ML models)
• Knowledge of DataOps and CI/CD practices for data pipelines.
• Ability to work independently and collaboratively in multidisciplinary teams.
• Good communication skills to translate business requirements into technical solutions.
• Analytical, proactive, and results-oriented profile.

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.