Data Engineer

Parkeet Ai is seeking a talented Data Engineer with a strong background in Python, SQL, ETL processes, and data warehousing. The ideal candidate will have a minimum of three years of experience in data engineering and will be responsible for designing, constructing, and maintaining our data architecture. This role involves a deep understanding of how to extract, transform, and load data from various sources into our databases and ensuring that the data is accurate and accessible for analytics and decision-making processes. Previous experience in a startup environment is advantageous, as it helps in adapting to our dynamic and fast-paced work culture. As a Data Engineer at Parkeet Ai, you will collaborate closely within our data team to develop robust data pipelines, optimize data storage, and improve data quality across various operations. You will be an integral player in shaping our data solutions and will help to drive insights that support our business growth. With no current team management responsibilities, this position allows you to focus on technical excellence and data project delivery in alignment with business objectives.

Responsibilities

Design and implement data pipelines to efficiently extract, transform, and load data from various sources into our data warehouses.
Ensure data integrity and quality throughout pipelines, addressing and resolving data discrepancies and issues.
Collaborate with data scientists and analysts to understand their data needs and provide the necessary datasets for analysis.
Maintain and optimize existing ETL processes to improve data flow and processing efficiency.
Monitor data processing activities and troubleshoot any issues that arise in the data engineering workflow.
Document data architecture, processes, and workflows to ensure knowledge sharing and compliance with industry standards.
Participate in data modeling efforts to support business reporting and future development.
Stay updated with the latest technologies and industry best practices in data engineering and analytics.
Support data governance initiatives to maintain data privacy and security across all platforms.
Contribute to cross-functional projects by providing data support and insights that aid in decision-making.