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EMC Insurance Companies · 7 hours ago

Staff Data Platform Engineer

United States

Full-time

Remote

Lead/Staff

$110K/yr - $174K/yr

10+ years exp

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.

Financial ServicesInsurance

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

Qualification

SnowflakeAWSAI/ML frameworksDBTData architectureData modelingAutomation frameworksData governanceCommunication skillsCollaboration skills

Required

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