The 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.

Basic Qualifications:
5+ years of relevant work experience with a Bachelor’s Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD, OR 8+ years of relevant work experience.

Preferred Qualifications:
5+ years of relevant work experience with a Bachelor’s Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD, OR 8+ years of relevant work experience.
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).

This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager.

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.