Lead Data Architect

Required Skills:

• Experience in Data Engineering, Analytics Engineering, Data Platforms, or related data & AI roles.
• Strong proficiency in Python for data engineering, automation, API integration, data transformation, and AI/ML solution development.
• Hands-on experience with modern Cloud Data Platforms such as Snowflake, Azure Data Factory (ADF), Microsoft Fabric, Advanced Analytics, Tableau or equivalent technologies.
• Expertise in designing and building scalable data pipelines to ingest, process, and manage structured, semi-structured, and unstructured data from files, APIs, databases, and cloud sources.
• Advanced SQL skills and experience working with relational databases such as SQL Server and cloud-native data warehouses.
• Experience leveraging Generative AI, Large Language Models (LLMs), AI Agents, Retrieval-Augmented Generation (RAG), Vector Databases, and AI-powered analytics solutions in enterprise environments.
• Proficiency in data visualization and analytics tools such as Power BI, Tableau, Python visualization libraries, and self-service analytics platforms.
• Experience implementing data quality frameworks, data observability, metadata management, data governance standards, and technical data catalogs/dictionaries.
• Familiarity with Machine Learning lifecycle concepts (MLOps) including model deployment, monitoring, prompt engineering, and responsible AI practices.
• Experience with DevOps, CI/CD, Infrastructure as Code (IaC), Git-based development workflows, and Agile/Scrum methodologies.
• Proficiency with collaboration and project management tools including Jira, Confluence, SharePoint, GitHub/GitLab, and Azure DevOps.
• Strong analytical thinking and innovative problem-solving skills with the ability to leverage AI-assisted development tools to accelerate delivery and improve productivity.
• Proven ability to rapidly learn and adopt emerging technologies in the evolving Data, Analytics, and AI landscape.
• Demonstrates a Team-First mindset, fostering collaboration and contributing to the maturity of enterprise Data, Analytics, and AI platforms.
• Experience in Financial Services, Banking, Credit Union, FinTech, or related regulated industries is preferred.
• Knowledge of data security, privacy, compliance, and Responsible AI governance within regulated environments is highly desirable.