The Role: Location: Charlotte, NC Hybrid: Monday-Thursday onsite and Friday Remote Reports to: Data Engineering Manager *All applicants must be currently authorized to work in the United States. No relocation allowance will be considered unless specifically addressed. Role Summary We are seeking a Data Engineer to drive Odyssey's enterprise data engineering strategy. This role will build, maintain, and improve scalable data pipelines, analytics-ready data models, and lakehouse solutions that power reporting, self-service analytics, and AI/ML use cases. This role also acts as an analytics consultant to business teams-partnering with stakeholders to translate business questions into data-driven solutions that drive measurable ROI, operational efficiency, and decision impact What You'll Do: Data Architecture & Engineering Build and maintain scalable data lake and lakehouse solutions that integrate diverse enterprise data sources into canonical models and curated datasets. Develop and operate batch and streaming pipelines that ensure reliable, performant, and accurate data delivery. Support both batch and near-real-time data processing for operational and analytical use cases. Development & Code Quality Write production-quality Python, SQL, and Spark code following engineering best practices. Contribute to CI/CD pipelines, version control workflows, and code reviews to maintain high-quality, secure deployments. Implement data validation, reconciliation, and basic observability to support data reliability and trust. Data Modeling & Analytics Enablement Develop analytics-ready data models - facts, dimensions, and metrics - that support self-service BI and reporting. Support Sigma Computing by maintaining semantic layers, datasets, and governed metrics for consistent business reporting. Collaborate with Analytics Engineers to define data transformations, metric logic, and data contracts Business Partnership & Consulting Act as an analytics consultant to business stakeholders by translating operational and strategic questions into scalable data and analytics solutions. Partner with functional teams across Sales, Finance, Operations, and Shared Services to identify high-impact use cases that drive measurable business outcomes. Help stakeholders understand data limitations, assumptions, and opportunities to maximize business value from analytics investments. Performance, Security & Compliance Optimize cloud compute and storage usage across Databricks and AWS to support cost efficiency. Apply secure-by-design practices including RBAC, encryption, and approved access controls. Operations & Support Troubleshoot pipeline failures, performance issues, and data inconsistencies and implement improvements. Support vendor tools and platforms through integrations, upgrades, and issue resolution. Maintain documentation for data pipelines, data models, and analytics datasets What You Bring: Technical Skills Strong SQL and query design experience including performance tuning, query optimization, and data validation across heterogeneous data sources. Hands-on proficiency in Python, SQL, and Scala; Java preferred. Experience with ML frameworks including Spark, Databricks, TensorFlow, scikit-learn, and PyTorch Cloud & Platform Experience Experience with cloud platforms - AWS required, Azure and GCP preferred - including services for storage, compute, orchestration, and monitoring. Experience with BI and analytics platforms such as Sigma Computing, Tableau, Power BI, or MicroStrategy to support self-service and operational reporting Data Governance & Security Understanding of data governance, data quality, lineage, and compliance requirements including GDPR and SOX. Hands-on application of RBAC, encryption, and secure-by-design practices in cloud environments Analytics & AI Ability to analyze large, complex, multi-dimensional datasets - structured and unstructured - to deliver insights and power advanced analytics and ML use cases. Familiarity with Generative AI concepts and modern ML techniques including LLMs, transformers, ensemble methods, and deep learning frameworks, and how they integrate into data engineering workflows Leadership & Collaboration Exceptional communication and leadership skills with the ability to mentor engineers, influence stakeholders, and drive adoption of data products and practices. Demonstrated ability to navigate ambiguity - driving clarity, alignment, and momentum in evolving requirements and complex stakeholder environments. Working knowledge of agile and scrum methodologies and tools such as Jira and Confluence. Problem Solving Strong analytical mindset capable of identifying patterns, optimizing processes, and unlocking new business value through scalable solutions Benefits We offer a comprehensive and competitive compensation and benefits package, including: • A choice of medical plans with FSA and HSA options • Dental Insurance • Vision Insurance • Company-paid Life and Disability Insurance • 401(k) Plan with Company Match • Paid Time Off (PTO) and Company Holidays • Employee Assistance Program • Company Health & Wellness Program • Discounts with Preferred Vendors