Data Engineer

Summary

Join Canibuild, a rapidly growing SaaS startup, as a Data Engineer. You will play a key role in designing, developing, and maintaining ELT pipelines using Python, Airflow, and SQL within an AWS environment. Responsibilities include creating and maintaining data visualizations and dashboards using PowerBI, connecting to our SQL Server and PostgreSQL Aurora databases. This position offers the opportunity to influence architectural decisions and contribute to the development of a data warehouse in a cloud-native environment. You will collaborate with stakeholders, implement best practices, and optimize database performance. The ideal candidate possesses extensive experience in data engineering, AWS, and PowerBI.

Requirements

• Expert-level proficiency in SQL (TSQL, MS SQL) with a strong focus on optimizing SQL queries for performance
• At least 7 years of experience will be preferred
• Extensive experience with Python and Airflow for ELT processes
• Proven experience in designing and developing data warehousing solutions on the AWS cloud platform
• Strong expertise in PowerBI for data visualization and dashboard creation
• Familiarity with connecting PowerBI to SQL Server and PostgreSQL Aurora databases
• Experience with REST APIs and JSON
• Agile development experience with a focus on continuous delivery and improvement
• Excellent problem-solving skills and a proactive “can-do” attitude
• Strong communication skills and the ability to work collaboratively in a team environment
• Curiosity and eagerness to learn and adapt to new technologies and methodologies
• Ability to perform database tuning and optimization to ensure efficient data operations

Responsibilities

• Design, develop, and maintain ELT pipelines using Python, Airflow, and SQL in an AWS environment
• Create and manage a data lake and data warehouse solutions on AWS
• Develop and maintain data-driven dashboards and reporting solutions in PowerBI
• Connect PowerBI to SQL Server and PostgreSQL Aurora databases using a gateway
• Perform data profiling and source system analysis to ensure data quality and integrity
• Collaborate with business stakeholders to capture and understand data requirements
• Implement industry best practices for data engineering and visualization
• Participate in architectural decisions and contribute to the continuous improvement of data solutions
• Follow agile practices and a Lean approach in project development
• Optimize SQL queries for performance and ensure efficient database operations
• Perform database tuning and optimization as needed

Preferred Qualifications

• Exposure to AWS Cloud Data Services such as RedShift, Athena, Lambda, Glue, etc
• Experience with other reporting tools like Tableau
• Knowledge of data lake architectures and best practices

Benefits

• Flexible work arrangements
• Full Time Remote Work
• Opportunity to grow with a fast-scaling company
• Recognition and reward for your contributions