Data Engineer IV

• 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 bachelors 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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