Blueground is hiring a
Analytics Engineer

Summary

Join Blueground's growing team as an Analytics Engineer to transform raw data into actionable insights, enabling the company to make informed decisions that drive business growth.

Requirements

• 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

Responsibilities

• Design, develop, and optimize data models to support reporting, analytics, and business intelligence
• Maintain and update existing data models as the business evolves
• 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
• Oversee the management and optimization of data warehouses to support analytics and reporting requirements
• Ensure data warehouses are scalable, reliable, and secure
• 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
• Work closely with business stakeholders to understand their data needs and translate them into technical requirements
• Stay updated on the latest trends and technologies in data engineering and analytics
• Continuously seek opportunities to improve data processes, tools, and methodologies