IT Data Engineer

Description

• Maintain a high regard for personal safety, the safety of company assets and employees, and the general public.
• Collaborate with security, compliance, and governance teams to ensure pipelines and databases meet corporate and regulatory requirements.
• Serve as lead administrator for enterprise databases, overseeing performance, clustering, backup, and recovery.
• Design, build, and maintain scalable data pipelines connecting enterprise systems to AI and analytics platforms.
• Implement and enforce database security controls, patching, access management, and encryption standards.
• Monitor and optimize data flows for consistency, scalability, latency, and data integrity across the ecosystem.
• Maintain regular, dependable attendance and a high level of performance.
• Track and report key operational metrics and continuously drive improvements to meet SLA and business objectives.
• Evaluate emerging technologies in data engineering, vector search, and graph-based relationships and recommend adoption where appropriate.
• Support ongoing AI and data modernization strategies by ensuring infrastructure, pipelines, and models are production-ready for next‑generation workloads.
• Develop retrieval-augmented generation (RAG) workflows and vectorized data models to improve AI information access.
• Recommend and implement process automation to reduce manual database and integration tasks and improve operational efficiency.
• Plan and execute the transition from external DBA vendor support to internal management within 12 months.
• Troubleshoot production incidents, perform root-cause analysis, and implement corrective actions to prevent recurrence.
• Provide guidance, mentoring, and knowledge transfer to operations and development teams to improve reliability and performance.
• Support application integrations, data migrations, and deployment of new data environments with minimal disruption.
• Build and maintain connectors and APIs for secure, high-performance data retrieval across on‑prem and cloud environments.
• Document data lineage, architecture diagrams, interfaces, and operational runbooks; keep documentation current.
• Define and maintain data models, schema standards, and metadata to support analytics and AI use cases.
• Apply and maintain best practices for high availability, disaster recovery, and change management.
• Manage database upgrades, tuning, capacity planning, and storage optimization for transactional and analytical workloads.
• Orchestrate large-scale data movement using cloud data platforms to ensure availability for AI and business applications.

Requirements

• Must have excellent communication, collaboration, and coordination skills to work cross‑functionally with security, development, and business stakeholders and to mentor peers.
• Understanding of semantic data modeling, graph relationships, or AI-driven retrieval architectures.
• Working understanding of vectorization, embeddings, and retrieval-based AI concepts.
• Familiarity with cloud-based data ecosystems and large-scale data orchestration.
• Must have hands‑on experience with retrieval‑augmented generation (RAG), vectorization/embeddings, and vector stores (or equivalent AI data modeling).
• Experience integrating enterprise systems such as ERP or document repositories into data platforms.
• Proficiency in MS Office applications that may include but are not limited to Excel, Word, SharePoint, PowerPoint, and Outlook.
• Must possess and maintain a valid driver’s license and a driving record satisfactory to the company and its insurers (for travel).
• 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.
• 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.
• Must have strong cloud and infrastructure skills, including infrastructure-as-code and container/orchestration familiarity.
• 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.
• May be required to carry a cell phone and be available to respond during working and non-working hours.
• Strong documentation skills.
• Proficiency in one or more scripting or automation languages (e.g., Python, PowerShell).
• Advanced knowledge of administering and optimizing enterprise relational and analytical databases (performance tuning, backup/recovery, replication/clustering, and capacity planning).
• Experience designing or supporting data pipelines that feed AI or advanced analytics platforms.
• Must be able to work with a team, take direction from management, adhere to require work schedules, and follow company policies.
• Must have strong analytical troubleshooting and root‑cause analysis skills to resolve production incidents and drive corrective actions.
• Experience modernizing or migrating traditional database workloads to cloud environments
• Strong technical foundation in SQL, data modeling, and performance optimization.
• Must have effective time management and prioritization skills to handle multiple projects, meet deadlines and deliverables.
• Minimum of 7 years of experience in database administration or data engineering within complex enterprise environments.
• Must have demonstrated competency in data governance and security, including metadata, data lineage, IAM, encryption, auditing, and regulatory/compliance alignment.
• Must be able to sit for prolonged periods of time.
• Knowledge of data governance frameworks and regulatory compliance related to data access and storage.
• Ability to design, build, and operate scalable batch and streaming data pipelines, connectors, and APIs that reliably serve AI and analytics workloads.
• Must have experience leading vendor-to-internal transitions or similar projects, including planning, knowledge transfer, and operationalizing in‑house support within defined timelines.

Benefits

• Company vehicle (if applicable)
• Networking and employee engagement events
• Vacation, sick days, paid caregiver leave, volunteer and bereavement paid time off
• Personal development to grow your career with us based on your strengths and interests
• Parental Leave
• Employer-paid life insurance, short-term disability, and long-term disability coverage
• Company-paid holidays and floating holidays
• Employee discounts; vehicles, tires, cellular plans, and more
• Annual discretionary bonus
• 401(k) with up to a 6% match that vests immediately plus an employer discretionary contribution of up to 4%
• Industry competitive pay
• Identity theft protection
• Infertility Coverage
• Health insurance package options that include Flexible Spending & Health Savings Accounts
• Wellness Programs and Mental Health Resources
• Critical Illness & Accident Insurance
• Generous Tuition Reimbursement Program

Training + Development

Interview process

Visa Sponsorship

Security clearance