• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a closely related field. A Master’s degree or equivalent experience is desirable.
• Experience designing and implementing enterprise-scale data warehouses, data lakes, and data integration pipelines. Skilled in data modeling, performance optimization, and automation of ingestion, transformation, and publishing processes.
• Experience architecting and deploying cloud-based data solutions using Microsoft Azure (preferred), AWS, or Google Cloud. Knowledge of networking, capacity planning, elasticity, and cost optimization in hybrid environments.
• Experience implementing security controls and data protection measures in compliance with state and federal privacy and security frameworks such as HIPAA, FedRAMP, or CJIS. Familiarity with role-based access, encryption, and audit practices.
• Experience establishing or supporting data governance processes, including data cataloging, metadata management, data lineage, classification, and quality management. Familiarity with tools such as Azure Purview, Collibra, or Informatica.
• Proficiency with data management and analytics technologies such as Snowflake, Azure Data Factory, SQL Server, Oracle, Power BI, Tableau, SAS Viya, or equivalent. Experience with DevOps practices and version control using Azure DevOps or Git.
• Experience in leading adoption of AI/ML or generative AI tools in an enterprise environment desired.
• Knowledge and preferably hands-on experience applying Generative Artificial Intelligence (Gen AI) technologies, Large Language Models (LLMs), and AI-assisted automation approaches to improve data engineering, data management, analytics, and software development processes. Experience leveraging Gen AI tools to automate repetitive data engineering tasks, enhance data quality, accelerate documentation, improve metadata management, or optimize data pipeline development is highly desirable.
• Demonstrated ability to partner with business, program, and IT teams to translate requirements into technical designs. Experience mentoring junior engineers and promoting best practices across cross-functional teams.
• Understanding of Agile and DevOps methodologies, project management principles, and CI/CD pipelines for data engineering.
• Strong analytical, problem-solving, and strategic thinking skills. Excellent communication, documentation, and stakeholder engagement abilities. Proven capacity to manage multiple priorities and deliver under tight deadlines.