Jobs at NucleusTeq

Lead multiple projects overseeing requirements to deployment, develop automation tools with Python and Selenium, and process unstructured data for insights. Create dashboards and apply statistical modeling to forecast trends.

The job requires a self-driven Data Engineer skilled in SQL, data modeling, and integration, along with a foundational understanding of Generative AI. Responsibilities include data extraction, transformation, and collaboration with teams.

The Software Engineer will assist in designing and developing applications, support backend services, and collaborate with team members to automate processes and troubleshoot issues.

The Data Scientist will develop high-performance AI/ML systems, manage data pipelines, and integrate AI services into cloud platforms. Requires strong technical skills and innovation.

The GCP & Big Data Engineer will design and maintain scalable data pipelines on Google Cloud, optimize data processing, and ensure data quality.

Design and maintain scalable data pipelines using Google Cloud services, ensure data quality, and collaborate with stakeholders to deliver data solutions.

Design, develop, and implement enterprise software. Analyze requirements and user stories, track work in Jira, write and test code, build integrations across UI, middleware, and backend, perform system and regression testing with JMeter/Insomnia/Postman, and deploy applications using Topaz and ServiceNow. Coordinate technical delivery and travel to US job sites as needed.

Perform deep-dive analytics using advanced SQL to analyze customer behavior, redemptions, and campaign performance. Build data validation frameworks, ensure accuracy of loyalty and financial metrics, and collaborate with Product, Marketing, and Engineering to validate feature rollouts and deliver data-driven insights.

Design and build production-grade GenAI systems using LLMs and RAG. Develop Python data pipelines with vector databases, optimize latency, perform prompt engineering and fine-tuning, integrate frameworks (LangChain, LlamaIndex, Hugging Face) into cloud (AWS/Azure/GCP), and implement automated testing, model monitoring, and reliability practices.

The Cloud DevOps Engineer is responsible for designing and managing AWS infrastructure, building CI/CD pipelines, and ensuring system performance while implementing security best practices.

The MicroStrategy Cloud Administrator will install, configure, and manage MicroStrategy in cloud environments, optimize performance, and ensure security and governance while collaborating with SRE/cloud teams and automating deployments.

As a Data Engineer, you'll optimize data pipelines and models using PySpark, SQL, and GCP. Responsibilities include processing large datasets and designing enterprise-scale data platforms.

The Lead/Senior Recruiter will drive IT hiring practices, manage full-cycle recruitment, and utilize AI tools to source candidates effectively.

Design and maintain scalable cloud data models and semantic layers, build and monitor ETL/ELT pipelines, develop conversational BI integrations with AI, and create insightful automated visualizations and dashboards to translate business requirements into actionable analytics.

The Software Developer oversees quality control, manages project scope, gathers requirements, and develops cloud architecture, while utilizing various programming and project management tools.

We are seeking Data Engineers to migrate dashboards from Hadoop to GCP, ensuring data consistency, accuracy, and collaborating with cross-functional teams.

The Technical Product Manager will manage the entire product lifecycle, lead Agile teams, translate business needs into actionable requirements, and collaborate with cross-functional teams, focusing on data-driven strategies in a B2B SaaS environment.

The Marketing Intern will support product marketing initiatives, manage social media accounts, create content, and assist in analytics and promotions.

The Vice President of Sales will drive growth by developing sales strategies, leading a sales team, and establishing partnerships in enterprise data and cloud services.

The Data Engineer will design optimized data systems, maintain data pipelines, integrate data sources, and automate workflows to support analytics and machine learning initiatives.