Job Title

We are seeking a Data Engineering Director to lead our data engineering team at DataMantis, a fast-growing AI company. This is a critical role where you will oversee the design, development, and implementation of scalable and innovative data pipelines and infrastructure to support our AI-driven SaaS product.As the Data Engineering Director, you will drive the architecture and strategy for all aspects of data engineering, from data integration and storage to advanced data modeling, AI frameworks, cloud architecture, and Prompt Engineering. You will lead the charge on cutting-edge technologies like Retrieval Augmented Generation (RAG) and AI data architectures, and play an integral part in scaling our data-driven operations to support the company’s growth.Key Responsibilities:Lead the Data Engineering Team: Oversee a high-performing team of data engineers, guiding them in designing and building reliable, scalable, and optimized ETL pipelines, data warehouses, and integrations.Architecture Design: Develop and implement data architectures that support AI-powered solutions, including Vectorization, Chunking, Ontologies, Knowledge Graphs, and Text-to-SQL conversion.Data Integration: Work closely with product and engineering teams to implement and optimize SaaS application connector frameworks for seamless data flow and integration.AI Frameworks: Utilize cutting-edge AI frameworks such as LangChain, LlamaIndex, Agentic AI, and RAG to develop and enhance data processing workflows, specifically for AI/ML-driven applications.Prompt Engineering: Lead the application of Prompt Engineering techniques to optimize interactions with AI models and improve the accuracy and efficiency of data pipelines, ensuring that data queries and processing are maximized for performance in AI/ML environments.Database Management: Lead initiatives in relational database management and design, with experience working in technologies like GraphQL and relational databases (e.g., Postgres SQL) and vector databases (e.g., Superbase).Cloud Infrastructure: Ensure optimal use of Azure Cloud infrastructure, including implementing robust data engineering solutions that scale effectively and efficiently in the cloud.Scalability & Performance: Architect horizontally scalable systems using Kubernetes, Spark/Dask, and serverless architectures. Monitor and tune costs for cloud storage, ETL, and compute.R&D and Innovation: Stay at the forefront of data engineering and AI technologies, researching and implementing new tools and methodologies to drive innovation in data architecture, AI applications, and Prompt Engineering.Stakeholder Collaboration: Work cross-functionally with product, engineering, and data science teams to ensure data systems support AI model development, data analytics, and business intelligence.Mentorship and Team Growth: Develop and mentor the team, fostering a culture of continuous improvement, collaboration, and high-quality engineering practices.Key Requirements:ETL Knowledge or SaaS Application Connector Frameworks: Proven experience in designing and implementing complex ETL pipelines and integrating SaaS applications using connector frameworks.Relational Database Management and GraphQL: Strong understanding of relational database management systems, and practical experience with GraphQL for data querying and management.Vector Databases Expertise: Hands-on experience working with vector databases like Superbase/Postgres SQL to support AI-driven applications and data processing.Retrieval Augmented Generation (RAG): Deep understanding of Retrieval Augmented Generation methodologies and experience applying them to AI systems.Prompt Engineering: Solid experience in applying Prompt Engineering best practices to improve AI interactions, optimize model performance, and enhance data pipeline processing.AI Data Architecture Expertise: Solid experience in designing and implementing AI-driven data architectures, including vectorization, chunking, ontologies, knowledge graphs, and Text to SQL.AI Frameworks Experience: Expertise in agentic AI frameworks, such as LangChain, LlamaIndex, or similar tools for data processing and AI model integration.Azure Cloud Expertise: Demonstrated experience with Azure Cloud services, including data storage, computing, and security best practices. Azure Data Engineer Certification is highly preferred.Leadership Experience: Strong track record of leading data engineering teams and projects in a SaaS or AI-driven company environment.Excellent Communication Skills: Ability to communicate complex technical concepts to non-technical stakeholders and collaborate with various teams to achieve business goals.Preferred Qualifications:Azure Data Engineer Certification or similar certifications in cloud data engineering.Advanced degree in computer science, data engineering, AI, or a related field.Prior experience working in an AI-first SaaS company.Why Join Us:Innovative and Growing Company: Join a company at the forefront of AI, working with cutting-edge technologies.Career Growth: Work in a fast-paced, growth-oriented environment with significant opportunities for professional advancement and skill development.Collaborative Culture: Join a talented, diverse, and dynamic team focused on solving complex challenges and delivering innovative solutions.Competitive Compensation: We offer a competitive salary and a flexible work environment.Equity Option: We are open to offering equity option on top of competitive salary.If you are passionate working for an AI startup, make a difference in data & Prompt Engineering, and leading teams to solve complex challenges, we want to hear from you. Apply today and be a part of a visionary AI company that’s shaping the future!