GCP Data Engineer

Job Description

Job Title: Data Engineer Location: Remote (Must be available to work in U.S. time zone until 4 PM PST) Job Type: Full-Time Experience Level: Mid-Level (5-7+ years) Position Overview: We are searching for a mid-level Data Engineer who also has a strong skill set in data analysis. This person will be instrumental in developing, building, and maintaining the infrastructure that allows us to make informed decisions based on accurate data analysis. Key Responsibilities: 1. Data Pipeline Development: - Build and optimize data pipelines using Python to efficiently gather and process large volumes of data. - Utilize Google Cloud services to store and manage data effectively. - Develop and maintain data storage solutions using Snowflake , ensuring data is accessible, reliable, and secure. 2. Data Modeling and Architecture: - Design and implement data models that support business needs and analytics capabilities. - Create visually appealing dashboards and reports using tools like Tableau and Google Looker to communicate data insights and trends clearly to stakeholders. 3. Data Integration and API Development: - Build and maintain data integrations with both internal and external data sources. - Develop Application Programming Interfaces (APIs) to ensure seamless data exchange between systems, making it easy to access and analyze data from various platforms. Required Qualifications: - 5-7+ years of experience in Data Engineering and Data Analysis roles. - Proficient in Python and experienced with data processing libraries. - Strong knowledge of Google Cloud and Snowflake. - Familiarity with data visualization tools like Tableau and Google Looker. - Experience with API development and data integration techniques. - Strong analytical thinking and problem-solving skills. - Ability to work independently and collaboratively as part of a team. Preferred Qualifications: - Bachelor’s degree in Computer Science, Data Science, or a related field. - Experience with ETL (Extract, Transform, Load) tools and practices. Show more Show less