Data Engineer

As a Data Engineer at Parket Ai, you play a pivotal role in developing and maintaining robust data pipelines and architectures. Your expertise in Python and SQL, combined with your experience in building effective ETL (Extract, Transform, Load) processes, enables you to transform raw data into meaningful insights. You work with data-centric projects that support the organization's goal of leveraging data analytics and artificial intelligence solutions. While prior experience in an AI startup is considered a valuable asset, your primary focus will be on implementing and optimizing data processes that facilitate data-driven decision-making and analytics initiatives. You will collaborate closely with data scientists, analysts, and stakeholders to ensure that data flow is seamless and efficient. Your contributions are essential for ensuring the accuracy, reliability, and availability of data for analysis and reporting purposes.

Responsibilities

Design, build, and maintain scalable data pipelines to ensure the smooth flow of data between various systems.
Develop and optimize ETL processes to extract data from various sources, transform it into a suitable format, and load it into data warehouses or databases.
Work collaboratively with data scientists and analysts to understand data requirements and deliver appropriate data solutions.
Implement data integration solutions to consolidate data from multiple sources, ensuring high data quality and reliability.
Monitor and troubleshoot data pipeline performance, identifying bottlenecks and improving efficiency as needed.
Utilize Python for scripting and automation tasks related to data processing and analysis.
Write complex SQL queries for data extraction and manipulation to support analytical needs.
Participate in the design and implementation of data models and databases that align with the company's data strategy.
Document data pipelines and processes to facilitate knowledge sharing and compliance with best practices.
Stay updated with emerging trends in data engineering and AI to drive innovation within data processes.