- Design and Build Pipelines: Create, maintain, and optimize scalable data pipelines that effectively handle the extraction of raw data from various sources, its transformation into a consistent format, and its loading into destinations for analysis and reporting.
- Develop Transformation Logic: Implement algorithms and logic to clean, standardize, and transform data into a consistent and actionable format, preparing it for downstream use.
- Integrate Data: Combine raw information from diverse sources to create unified, comprehensive datasets for analytical purposes.
- Implement Quality Checks: Design and implement robust data validation processes, data quality checks, and error handling procedures to guarantee the accuracy, completeness, and reliability of datasets.
- Ensure Consistency: Work to maintain data consistency across various systems and ensure the data is reliable for business decision-making.
- Optimize Data Infrastructure: Develop and manage data architecture, including databases and data warehouses, to ensure efficient storage, quick retrieval, and accessibility of data.
- Collaborate with Stakeholders: Partner closely with data scientists, analysts, and other teams to understand their data requirements and deliver high-quality, ready-to-use datasets for their projects.
- Performance Tuning: Optimize database and query performance through fine-tuning, indexing, and other strategies to ensure data processing and retrieval are fast and resource-efficient.
- Manages critical projects, customer engagements or business processes and advises junior team members.
- Responsible for mentoring developers with code reviews, design reviews and unit test plan reviews.
- Performs other duties as assigned.
- Typically requires a bachelor’s degree in computer science, software engineering, or a related field and eight (8) or more years of related experience; or an equivalent combination.
- Cloud data engineering experience (Google Cloud Platform, AWS, Azure or similar)
- SQL
- Python
- AI/ML
- Ability to automate and operationalize machine learning workflows.
- Applies knowledge to analyze and develop solutions to highly complex problems.
- Develops and maintains a thorough knowledge of key business processes, current and future requirements, and key success factors.
- Thorough understanding of key business drivers and ability to communicate and translate those needs to technical solutions.
- Ability to collaborate effectively with senior management.
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GPC conducts its business without regard to sex, race, creed, color, religion, marital status, national origin, citizenship status, age, pregnancy, sexual orientation, gender identity or expression, genetic information, disability, military status, status as a veteran, or any other protected characteristic. GPC's policy is to recruit, hire, train, promote, assign, transfer and terminate employees based on their own ability, achievement, experience and conduct and other legitimate business reasons.
What We Do
Genuine Parts Company (GPC), founded in 1928, is a global service organization engaged in the distribution of automotive and industrial replacement parts. We serve hundreds of thousands of customers from a network of more than 10,000 locations in 14 countries and have approximately 50,000 employees.
