Senior Data Engineer

W2 ONLY - No C2C will be considered Senior Data Engineer (multiple openings) Las Vegas, NV (onsite, hybrid, or remote - must be PST) 6 Month Project Our prestigious $1B revenue per year client is seeking Senior Data Engineers to join their cutting-edge team, driving forward-thinking technology solutions for the future. This opportunity has the potential to convert into a salaried role. The Senior Data Engineers will be responsible for designing, building, and managing the data platform and tools to allow for the efficient processing and analysis of large data sets. Develops and maintains scalable data pipelines, ensures data quality, and deploys machine learning models to production. Collaborates with business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision-making across the organization. Builds real-time and batch pipelines to handle large volumes of data efficiently. Collaborates with cross-functional teams and translate business requirements into scalable data solutions. Responsibilities: Design, develop, and maintain real-time or batch data pipelines to process and analyze large volumes of data. Designs and develops programs and tools to support ingestion, curation, and provisioning of complex first party and third-party data to achieve analytics, reporting, and data science. Design and develop Advanced Data Products and Intelligent API’s. Monitors the system performance by performing regular tests, troubleshoots, and integrates new features. Lead in analysis of data and the design the data architecture to support BI, AI/ML and data products. Designs and implements data platform architecture to meet organization analytical requirements. Ensures the solution designs address operational requirements such as scalability, maintainability, extensibility, flexibility, and integrity. Provide technical leadership and mentorship to team members. Leads peer development and code reviews with focus on test driven development and Continuous Integration and Continuous Development (CICD). Requirements: Bachelor’s degree in computer science, information systems, data science, management information systems, mathematics, physics, engineering, statistics, economics, or a related field required. Master’s degree in the same fields preferred. Minimum of 8 years as a data engineer with full-stack capabilities. Minimum of 10 years in programming. Minimum of 5 years in cloud technologies such as Azure, AWS, or Google Cloud. Hands-on experience with Databricks, Spark, Fabric, or similar technologies. Extensive experience with Big Data technologies (e.g., Apache Spark) and streaming technologies (e.g., Kafka, EventHub). Proven expertise in data pipeline design and development, data ingestion, processing, and analytical pipelines for big data, NoSQL, and data warehouse solutions. Significant experience in cloud-based data applications and infrastructure. Proficiency in Python and CI/CD practices. Experience in data migration and processing using Azure services (e.g., ADLS, Azure Data Factory, Event Hub, IoT Hub, Azure Stream Analytics, Databricks, Azure Data Catalog, Cosmo DB, ML Studio, AI/ML, etc.). Skills: Strong SQL knowledge. Experience in machine learning (ML) and ML pipelines. Proficiency in real-time integration, developing intelligent apps, and data products. Extensive background in data architecture, data modeling, and data quality frameworks. Knowledge of BI tools such as Power BI and Tableau. Advanced understanding of data security best practices, systems, and data integration architecture. Intermediate experience with RESTful APIs, messaging systems, and cloud services.