<p>Primary purpose:</p> <p>The AI Data Engineer will bridge traditional database administration with emerging AI data infrastructure to advance AI and data modernization initiatives. This role combines AI Data Engineering and Integration, designing scalable pipelines, RAG workflows, vectorized models and secure connectors, with Database Administration and Infrastructure duties as the lead administrator responsible for performance, backup and recovery, upgrades and the transition from third party DBA support to an internal capability. The position also owns Data Governance and Reliability by defining schemas, metadata and data lineage and by aligning pipelines with security and compliance requirements for high availability and disaster recovery. Finally, the role drives Continuous Improvement and Innovation by evaluating emerging technologies, implementing automation and enabling teams to support next generation AI workloads.</p> <p>Essential duties and responsibilities</p> <ul> <li>Design, build, and maintain scalable data pipelines connecting enterprise systems to AI and analytics platforms. </li><li>Develop retrieval-augmented generation (RAG) workflows and vectorized data models to improve AI information access. </li><li>Build and maintain connectors and APIs for secure, high-performance data retrieval across on-prem and cloud environments. </li><li>Orchestrate large-scale data movement using cloud data platforms to ensure availability for AI and business applications. </li><li>Monitor and optimize data flows for consistency, scalability, latency, and data integrity across the ecosystem. </li><li>Serve as lead administrator for enterprise databases, overseeing performance, clustering, backup, and recovery. </li><li>Manage database upgrades, tuning, capacity planning, and storage optimization for transactional and analytical workloads. </li><li>Plan and execute the transition from external DBA vendor support to internal management within 12 months. </li><li>Implement and enforce database security controls, patching, access management, and encryption standards. </li><li>Support application integrations, data migrations, and deployment of new data environments with minimal disruption. </li><li>Define and maintain data models, schema standards, and metadata to support analytics and AI use cases. </li><li>Collaborate with security, compliance, and governance teams to ensure pipelines and databases meet corporate and regulatory requirements. </li><li>Document data lineage, architecture diagrams, interfaces, and operational runbooks; keep documentation current. </li><li>Apply and maintain best practices for high availability, disaster recovery, and change management. </li><li>Evaluate emerging technologies in data engineering, vector search, and graph-based relationships and recommend adoption where appropriate. </li><li>Recommend and implement process automation to reduce manual database and integration tasks and improve operational efficiency. </li><li>Support ongoing AI and data modernization strategies by ensuring infrastructure, pipelines, and models are production-ready for next-generation workloads. </li><li>Troubleshoot production incidents, perform root-cause analysis, and implement corrective actions to prevent recurrence. </li><li>Provide guidance, mentoring, and knowledge transfer to operations and development teams to improve reliability and performance. </li><li>Track and report key operational metrics and continuously drive improvements to meet SLA and business objectives. </li><li>Collaborate with a variety of people with tact, courtesy, and professionalism. </li><li>Maintain regular, dependable attendance and a high level of performance. </li><li>Maintain a high regard for personal safety, the safety of company assets and employees, and the general public. </li><li>Other daily, weekly, monthly, or special projects may be assigned. </li></ul> <p>Minimum requirements:</p> <p>Education:</p> <p>Bachelor's degree from an accredited institution in Computer Science, Data Science, Computer Engineering, Information Systems or a related discipline, or five years equivalent experience.</p> <p>Experience/Specific Knowledge:</p> <ul> <li>Minimum of 7 years of experience in database administration or data engineering within complex enterprise environments. </li><li>Advanced knowledge of administering and optimizing enterprise relational and analytical databases (performance tuning, backup/recovery, replication/clustering, and capacity planning). </li><li>Strong technical foundation in SQL, data modeling, and performance optimization. </li><li>Experience designing or supporting data pipelines that feed AI or advanced analytics platforms. </li><li>Familiarity with cloud-based data ecosystems and large-scale data orchestration. </li><li>Must have hands-on experience with retrieval-augmented generation (RAG), vectorization/embeddings, and vector stores (or equivalent AI data modeling). </li><li>Working understanding of vectorization, embeddings, and retrieval-based AI concepts. </li><li>Proficiency in one or more scripting or automation languages (e.g., Python, PowerShell). </li><li>Must have experience leading vendor-to-internal transitions or similar projects, including planning, knowledge transfer, and operationalizing in-house support within defined timelines. </li><li>Proficiency in MS Office applications that may include but are not limited to Excel, Word, SharePoint, PowerPoint, and Outlook. </li></ul> <p>Certifications, Licenses & Registrations:</p> <ul> <li>Must possess and maintain a valid driver's license and a driving record satisfactory to the company and its insurers (for travel). </li></ul> <p>Competencies, Skills & Abilities:</p> <ul> <li>Ability to design, build, and operate scalable batch and streaming data pipelines, connectors, and APIs that reliably serve AI and analytics workloads. </li><li>Must have strong cloud and infrastructure skills, including infrastructure-as-code and container/orchestration familiarity. </li><li>Must have demonstrated competency in data governance and security, including metadata, data lineage, IAM, encryption, auditing, and regulatory/compliance alignment. </li><li>Must have the ability to implement automation, monitoring, and observability (CI/CD, scripting, Prometheus/Grafana or similar) and maintain runbooks to improve reliability and incident response. </li><li>Strong documentation skills. </li><li>Must have strong analytical troubleshooting and root-cause analysis skills to resolve production incidents and drive corrective actions. </li><li>Must have excellent communication, collaboration, and coordination skills to work cross-functionally with security, development, and business stakeholders and to mentor peers. </li><li>Must have effective time management and prioritization skills to handle multiple projects, meet deadlines and deliverables. </li><li>Must be able to work with a team, take direction from management, adhere to require work schedules, and follow company policies. </li></ul> <p>Physical Demands:</p> <p>All the physical requirements listed below are those that may be necessary for an employee to successfully perform the essential function of this job. Reasonable accommodations may be made for individuals with disabilities to perform the essential functions.</p> <ul> <li>Must be able to sit for prolonged periods of time. </li><li>The employee is regularly required to use hands to type, touch, handle, or feel. The employee is required to talk and hear. The employee is frequently required to stand and reach with hands and arms. The employee is occasionally required to walk and climb or balance. The employee must regularly lift and /or move up to 10 pounds and occasionally lift and/or move up to 25 pounds. </li></ul> <p>Working Conditions:</p> <ul> <li>Will work non-traditional hours as needed. </li><li>May be required to carry a cell phone and be available to respond during working and non-working hours. </li><li>Candidates will be required to clear a drug screen and complete a background check, including a credit report for certain positions after an offer has been extended and prior to being employed. </li></ul> <p>Supervisory Responsibility:</p> <ul> <li>None. </li></ul> <p>Preferred Education, Experience, Certifications, Competencies, Skills & Abilities:</p> <p>Above the minimum requirements, not required but advantageous in this position:</p> <ul> <li>Experience integrating enterprise systems such as ERP or document repositories into data platforms. </li><li>Knowledge of data governance frameworks and regulatory compliance related to data access and storage. </li><li>Understanding of semantic data modeling, graph relationships, or AI-driven retrieval architectures. </li><li>Experience modernizing or migrating traditional database workloads to cloud environments </li></ul> <p>Compensation</p> <p>The salary range for this role is $125,500-$164,500/yr.</p>