Data Engineer IV

Genuine Parts Company•Birmingham, AL

19h

About The Position

The Data Engineer IV performs complex data operations focusing on transformation and quality. This includes designing and building data pipelines for ETL (Extract, Transform, Load) processes, cleaning and transforming raw data into a usable format, implementing data validation and quality checks to ensure accuracy and reliability, optimizing data storage and retrieval for performance, and collaborating with data scientists to ensure data readiness for analytics and machine learning. The role also involves managing critical projects, customer engagements or business processes, and advising junior team members, including mentoring developers with code reviews, design reviews, and unit test plan reviews. Candidates must be eligible to work in the US without Visa Sponsorship.

Requirements

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.
Must be eligible to work in the US without Visa Sponsorship.
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.

Responsibilities

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.