Analytics Enginner Pleno

We are seeking a highly skilled and detail-oriented Analytics Engineer to join our growing team. The ideal candidate will play a crucial role in transforming raw data into actionable insights, enabling the company to make informed decisions that drive business growth. As an Analytics Engineer, you will collaborate closely with the data team and business stakeholders to design, implement, and maintain robust data models and analytics solutions.

Key Responsibilities:

1. Data Modeling:

• Design, develop, and optimize data models to support reporting, analytics, and business intelligence.
• Maintain and update existing data models as the business evolves.

1. ETL Development:

• Develop, test, and maintain ETL (Extract, Transform, Load) processes to ensure the accurate and timely flow of data from various sources into data warehouses.
• Collaborate with data engineering to ensure the quality and reliability of data pipelines.

1. Data Warehousing:

• Oversee the management and optimization of data warehouses to support analytics and reporting requirements.
• Ensure data warehouses are scalable, reliable, and secure.

1. Reporting & Dashboards:

• Design and develop dashboards and reports using Google Looker Studio to provide actionable insights to stakeholders.
• Ensure that dashboards are user-friendly and meet the needs of various business units.

1. Collaboration:

• Work closely with business stakeholders to understand their data needs and translate them into technical requirements.

1. Continuous Improvement:

• Stay updated on the latest trends and technologies in data engineering and analytics.
• Continuously seek opportunities to improve data processes, tools, and methodologies.

Qualifications:

• Bachelor’s degree in Computer Science, Data Science, Engineering, Economics, Statistics or a related field.
• 2+ years of experience in a data engineering, analytics engineering, or a similar role.
• Proficiency in SQL and experience with data modeling tools.
• Knowledge in Python for data analysis and extraction.
• Experience with ETL tools (e.g., Airflow).
• Strong understanding of data warehousing concepts and technologies (e.g. BigQuery or similar).
• Experience with Google Looker Studio or similar tool.
• Familiarity with cloud platforms (e.g., AWS, Google Cloud) is a plus.
• Familiarity with Scrapers, APIs, DBT and Git are a plus
• Strong problem-solving skills and attention to detail.
• Excellent communication and collaboration skills.