Staff Data Platform Engineer

EMC Insurance Companies is a collaborative organization focused on making an impact. They are seeking a Staff Data Platform Engineer to design and evolve their data platform while ensuring performance and scalability for analytics and AI workloads.

Responsibilities:

• Designs and evolves the data platform using Snowflake, DBT, Sigma, and AWS (Glue, Lambda, SageMaker), ensuring performance, modularity, and scalability for analytics and AI workloads
• Creates and communicates clear architecture direction for software and product team services, which build upon and improve operational effectiveness and efficiencies
• Designs infrastructure and workflows that support machine learning and generative AI use cases, including semantic modeling, feature engineering, and model deployment pipelines
• Identifies trends in technology and anticipates new requirements; recommends and supports strategies to leverage emerging and innovative technologies
• Builds and maintains sandbox environments for experimentation with predictive models, LLMs, and real-time analytics using Snowflake ML and AWS AI services
• Guides integration of machine learning and generative AI into data pipelines and analytics workflows, enabling use cases like semantic search, predictive modeling, and intelligent automation
• Recommends and presents technology applications strategy to meet the current and future needs of respective business areas
• Ensures foundational patterns (e.g., DBT macros, ML preprocessing frameworks) align with enterprise architecture and support AI/ML scalability, governance, and compliance
• Recommends and supports the technical strategy and alignment of data platform capabilities with the business objectives of EMC
• Partners with Data Platform Operations, Information Security, Network, Cloud Engineering, and DevOps teams to lead the design and implementation of new business initiatives as related to data and analytics
• Partners with Platform Operations, Analytics Engineering, and DAP teams to embed AI-ready data platform(s) into data products and ensure alignment with business outcomes
• Serves as a subject matter expert in data analytics platform(s) and AI/ML strategy, influencing platform innovation and guiding teams on best practices for scalable, intelligent data systems
• Serves as a technical resource for Data Platform team members on complex questions or issues
• Designs and recommends software engineering governance policies, procedures, and roles, including proper development techniques and quality management following established SDLC procedures
• Partners with Information Security to create and maintain security and procedures aligned and documented to risk management requirements
• Partners with Enterprise Architecture team to incorporate the creation of patterns and services into reference architecture and SDLC
• Provides guidance for building and maturing assigned solution platforms through automation and reusable processes
• Recommends and supports patterns that guide engineering team members in creating data solutions
• Enhances enterprise engineering practices by sharing expertise in creating engineering processes, alerting, and metrics
• Performs other duties as assigned

Requirements:

• Bachelor's degree, preferably in computer science, data science, engineering, or related field, or equivalent relevant experience
• Ten years of experience in data architecture, data engineering, or advanced analytics or related experience
• Excellent ability to design enterprise data architectures using tools such as Snowflake, DBT, and AWS
• Deep understanding of analytics platforms (e.g., Sigma Computing) and data modeling principles
• Strong proficiency in AI/ML tools and frameworks, including Python, scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, AWS SageMaker, Snowflake ML, SQL-based predictive modeling
• Excellent knowledge of semantic modeling, feature engineering, model interpretability, and MLOps
• Advanced ability to translate business needs into scalable, AI-enabled technical solutions
• Familiarity with modular architecture, automation frameworks, and data governance
• Excellent communication and collaboration skills across technical and business stakeholders
• Experience defining high-level data architecture or technical vision for large projects