Data Analyst

Data Associate Analyst

Location: Bogotá - Colombia

About the Role:

The Data Science Solutions team is launching a new global hub in Colombia and seeks talented data analysts to build a high-impact function from the ground up.

As a Data Analyst on the Model Automation & Production team, you will support the creation and maintenance of batch data processes, ETL pipelines, and dashboards that enable model operations, monitoring, and reporting. You will work closely with data scientists, data engineers, and business stakeholders to ensure data is reliable, well-structured, and ready to support modeling and analytics use cases.

This role is ideal for someone who enjoys working with data, solving operational problems, and learning how business data is organized across systems and workflows. You will gain exposure to data pipelines, cloud platforms, workflow orchestration, and the insurance domain while building a strong foundation in data analytics and production support.

Key Responsibilities:

• Write clean and efficient Python and SQL code for data wrangling, transformation, and validation.
• Support the development and maintenance of batch data pipelines used for model operations, monitoring, reporting, and data quality checks.
• Work with structured data to perform extraction, transformation, and analysis.
• Assist in building and maintaining ETL workflows using orchestration tools such as Airflow.
• Help create and manage dashboards for model health monitoring and operational visibility, including Power BI or similar tools.
• Contribute to documentation, data mapping, and process diagrams to improve operational clarity.
• Participate in issue resolution, root cause analysis, and continuous improvement of data workflows.
• Build domain knowledge in insurance and financial services to better understand the structure and meaning of data.

Skills and Experience:

• Fluency in English and Spanish (Must)
• Bachelor’s degree in Engineering, Data Science, Mathematics, Statistics, Computer Science, Economics, or a related quantitative field.
• 0-4+ years of relevant experience, internships, or equivalent academic/project experience.
• Strong proficiency in Python and SQL.
• Strong data intuition, including the ability to clean, reconcile, and combine data from multiple sources while understanding granularity and structure
• Good communication skills and ability to work effectively with technical and non-technical stakeholders. Capacity to work collaboratively in cross-functional and global environments.
• Strong problem-solving mindset and curiosity to understand how business data is structured and used.
• Fast learner with the ability to quickly adapt to new tools, datasets, and business processes

Preferred / Nice to Have

• Ability to draw process diagrams or document workflows clearly.
• Experience or exposure to Spark
• Exposure to Airflow or other workflow orchestration tools.
• Knowledge of ETL, data pipeline development, and batch processing.
• Understanding of data modeling, warehousing concepts, and relational databases.
• Exposure to NoSQL databases such as MongoDB.
• Familiarity with Git and CI/CD practices.
• Experience with Power BI or other dashboarding/reporting tools.
• Interest in or exposure to insurance or financial services.
• Comfort working with data engineering teams and production data environments.