Job
Description
Work Responsibilities The Palantir Developer will be responsible for designing and implementing modern data architecture solutions that facilitate enterprise-level transformation. Key responsibilities include: Data Architecture Design: Create and optimize modern data architectures that support advanced analytics and operational requirements. Pipelining: Develop and maintain efficient data pipelines using Palantir Foundry to ensure seamless data flow and accessibility for analytics. Advanced Analytics: Create and deploy advanced analytics products that provide actionable insights to stakeholders, enhancing decision-making processes. Artificial Intelligence Integration: Collaborate with data scientists to incorporate AI and machine learning models into data pipelines and analytics products, enabling predictive capabilities. Agentic AI Exposure: Leverage knowledge of Agentic AI to develop systems that can autonomously make decisions and take actions based on data insights, enhancing operational capabilities. Collaboration: Work closely with cross-functional teams, including data scientists, engineers, and business analysts, to gather requirements and deliver tailored solutions. Cloud Technologies: Utilize cloud-based tools and services to enhance scalability, security, and performance of data solutions. Best Practices: Implement best practices for data governance, quality, and security to maintain data integrity and compliance with relevant regulations. Continuous Improvement: Identify opportunities for process improvements and automation to enhance operational efficiency within data ecosystems. Documentation: Maintain comprehensive documentation of data architecture designs, pipeline configurations, and analytics processes. The Team Artificial Intelligence & Data Engineering: In this age of disruption, organizations need to embrace data-driven decision-making to Deliver Enterprise Value. Our Team Leverages Data, Analytics, Robotics, And Cognitive Technologies To Uncover Insights And Drive Transformation In Business. Key Initiatives Include Data Ecosystem Implementation: Collaborate with clients to implement large-scale data ecosystems that integrate structured and unstructured data for comprehensive insights. Predictive Analytics: Utilize machine learning and predictive modeling techniques to derive actionable insights and predict future scenarios. AI Solutions Development: Work on developing AI-driven solutions that enhance data analytics capabilities, including natural language processing (NLP), computer vision, and recommendation systems. Agentic AI Development: Engage in projects that involve the development and deployment of Agentic AI systems capable of autonomous decision-making and action-taking based on real-time data. Operational Efficiency: Drive operational efficiency by utilizing automation and cognitive techniques for data management, ensuring timely and accurate reporting. Client Engagement: Engage with clients to understand their unique challenges and tailor solutions that align with their strategic objectives. Innovative Solutions: Research and implement innovative technologies and methodologies that enhance data analytics capabilities and drive business value. Training and Support: Provide training and support to clients on data tools and platforms to ensure they can maximize the value of their data assets. Qualifications Required: Education: Bachelors degree in Computer Science, Data Science, Engineering, or a related field. Experience 3+ years of hands-on experience in data extraction and manipulation using various tools and programming languages. 3+ years of experience in engineering and developing Palantir pipelines, with a strong understanding of data integration techniques. 3+ years of experience collaborating with Palantir Foundry data scientists and engineers on complex data projects. 2+ years of experience working with AI and machine learning technologies, including model development, deployment, and performance tuning. Familiarity with Agentic AI concepts and applications, including experience developing or working with autonomous systems is a plus. Technical Skills: Proficiency in programming languages such as Python, SQL, or R, along with experience in statistical analysis and machine learning techniques. Problem-Solving: Strong analytical and problem-solving skills, with the ability to think critically and creatively. Communication: Excellent interpersonal and communication skills to effectively convey technical concepts to non-technical stakeholders.
