Brooksource · 2 days ago

Data Engineer, AI Solution Implementation

United States

Contract

Remote

Mid Level

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Responsibilities

Architect, design, and implement data pipelines and infrastructure to support the implementation of an AI solution at a large retail customer, leveraging Google Cloud Platform (GCP) technologies, including Gemini and VertexAI.

Collaborate with cross-functional teams to understand project requirements, translate them into technical specifications, and develop scalable and efficient data solutions.

Build and maintain data ingestion, transformation, and storage systems using GCP services such as BigQuery, Dataflow, and Cloud Storage, ensuring data quality, reliability, and security.

Develop and optimize machine learning pipelines for model training and inference, integrating with Gemini and VertexAI for seamless AI model deployment and management.

Work closely with AI engineers and data scientists to preprocess and prepare data for machine learning models, performing feature engineering, data augmentation, and exploratory data analysis as needed.

Implement monitoring, logging, and alerting mechanisms to track data pipeline performance and ensure timely identification and resolution of issues.

Collaborate with GCP technical experts and consultants to leverage best practices and optimize the use of Gemini and VertexAI tools and services for AI solution implementation.

Document data engineering processes, workflows, and best practices, and provide guidance and support to project team members as needed.

Qualification

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Data EngineeringCloud EnvironmentsGoogle Cloud Platform (GCP)BigQueryDataflowCloud StorageAI PlatformApache BeamTensorFlowData PreprocessingFeature EngineeringData ModelingMachine LearningAI ApplicationsPythonJavaScalable Code DevelopmentData GovernanceComplianceSecurity Best PracticesRetail IndustryProblem-SolvingAnalytical SkillsCommunicationCollaboration

Required

Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.

Proven experience in data engineering, with a focus on building data pipelines and infrastructure in cloud environments, preferably on Google Cloud Platform (GCP).

Strong proficiency in GCP services such as BigQuery, Dataflow, Cloud Storage, and AI Platform, as well as related technologies like Apache Beam and TensorFlow.

Experience with data preprocessing, feature engineering, and data modeling techniques, particularly in the context of machine learning and AI applications.

Proficiency in programming languages such as Python or Java, with experience in developing scalable and efficient data processing code.

Familiarity with data governance, compliance, and security best practices, especially in regulated industries such as retail.

Excellent problem-solving and analytical skills, with the ability to troubleshoot complex data engineering issues and optimize performance.

Effective communication and collaboration skills, with the ability to work in cross-functional teams and interact with stakeholders at all levels.