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Director Database Jobs in Elmhurst, IL (NOW HIRING)

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Director Database information

See Elmhurst, IL salary details

$51.8K

$128K

$199.2K

How much do director database jobs pay per year?

As of Aug 18, 2026, the average yearly pay for director database in Elmhurst, IL is $128,009.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,600.00 and $162,800.00 per year, depending on experience, location, and employer.

What does a director of database do?

A Director of Database oversees the management, security, and strategy of an organization's databases. They are responsible for ensuring data integrity, availability, and scalability to support business operations. This role often involves leading a team of database administrators and developers, setting database policies, and collaborating with other IT and business leaders to optimize data systems. Additionally, they may evaluate and implement new database technologies to align with organizational goals.

What are the key skills and qualifications needed to thrive as a director of database?

To thrive as a Director of Database, you need deep expertise in database architecture, management, and optimization, typically supported by a degree in computer science or a related field and substantial leadership experience. Familiarity with major database systems (such as Oracle, SQL Server, or MySQL), cloud platforms, and relevant certifications like AWS Certified Database – Specialty are often required. Strong strategic thinking, communication, and team leadership skills set outstanding candidates apart. These competencies are crucial for ensuring data integrity, system scalability, and the effective management of database teams in support of organizational goals.

What are some typical challenges a director of database faces when managing large-scale database systems?

A Director of Database often encounters challenges such as ensuring high availability and performance of database systems, managing data security and compliance, and overseeing the integration of new technologies. Balancing business requirements with technical constraints, coordinating across multiple teams—including developers, DevOps, and data analysts—and planning for disaster recovery are also common aspects of the role. Staying updated on industry best practices and leading initiatives to optimize database efficiency are essential to success in this leadership position.

What is the difference between Director Database vs Database Manager?

AspectDirector DatabaseDatabase Manager
CredentialsBachelor's or Master's in Computer Science, Information Technology, or related; often with certifications like CDMP or Oracle certificationsBachelor's in Computer Science, Information Technology, or related; certifications like Oracle or Microsoft SQL Server are common
Work EnvironmentStrategic leadership in large organizations, overseeing multiple teams and projectsOperational management of database systems, ensuring performance, security, and maintenance
Industry UsageUsed in enterprise-level companies, tech firms, and large organizationsCommon across industries for day-to-day database operations

The main difference between a Director Database and a Database Manager lies in scope and focus. The Director Database typically handles strategic planning and leadership at a higher level, while the Database Manager focuses on daily operations and technical management of databases.

What are the most commonly searched types of Database jobs in Elmhurst, IL?

The most popular types of Database jobs in Elmhurst, IL are:

What job categories do people searching Director Database jobs in Elmhurst, IL look for?

The top searched job categories for Director Database jobs in Elmhurst, IL are:

What cities near Elmhurst, IL are hiring for Director Database jobs?

Cities near Elmhurst, IL with the most Director Database job openings:

Infographic showing various Director Database job openings in Elmhurst, IL as of August 2026, with employment types broken down into 2% As Needed, 80% Full Time, 15% Part Time, 1% Temporary, and 2% Contract. Highlights an 90% Physical, 4% Hybrid, and 6% Remote job distribution, with an average salary of $128,009 per year, or $61.5 per hour.

Cloud Solutions Architect / Database Engineer / AI Platform Architect

ABCO MAINTENANCE INC. (BIC# 1854)

Aurora, IL • On-site

$150K - $180K/yr

Full-time

Posted 11 days ago


Job description

We are seeking a highly experienced Cloud Solutions Architect / Database Engineer / AI Platform Architect to design and build the cloud, database, security, API, and AI infrastructure that supports our enterprise applications. Compensation for thisrole will bebetween $150k-$180k depending on experience. This role will be responsible for establishing scalable cloud architecture, designing and engineering production databases, developing secure APIs and integration services, implementing authentication and application security standards, and architecting the AI foundation of our applications.

The architect will build the backend and AI service layers that allow front-end developers to securely and efficiently consume application data, business functionality, and AI-powered capabilities.The ideal candidate will have deep expertise in cloud architecture, C#/.NET, SQL Server, database engineering, REST APIs, application security, authentication, Azure or AWS, enterprise integrations, and production AI architecture . This individual should be capable of taking business and application requirements and translating them into secure, scalable, production-ready technical solutions. Experience with AI and Large Language Model (LLM) platforms is required, particularly when designing the infrastructure, data access, security, APIs, and application architecture necessary to support AI-powered enterprise solutions

The ideal candidate will have hands-on experience building production AI applications using OpenAI, Azure OpenAI, Anthropic, Google AI, or comparable LLM technologies, including designing workflows that enable AI to execute complex business processes through structured instructions, examples, retrieval strategies, orchestration, and enterprise data integration. This role requires experience developing AI as an operational component of an application, not simply integrating an AI API or adding chatbot functionality. Responsibilities Architect and implement scalable, secure, and highly available cloud environments for enterprise applications.

Design the overall backend architecture supporting web applications, internal systems, integrations, and AI-powered solutions. Design, build, and maintain production database environments, including schemas, tables, relationships, stored procedures, views, indexing strategies, and data-access patterns. Develop and optimize SQL Server databases for performance, scalability, reliability, data integrity, and security.

Establish database standards covering data modeling, normalization, indexing, query optimization, auditing, backup, recovery, and disaster recovery. Design and develop secureRESTful APIs and backend services using C#, ASP.NET Core, and related .NET technologies. Build well-structured API and service layers that allow front-end developers to consume data and business functionality without requiring direct access to backend systems or databases

Define API contracts, request/response models, validation standards, error handling, versioning, documentation, and integration patterns. Implement authentication and authorization solutions using technologies and standards such asOAuth 2.0, OpenID Connect, JWT, SSO, RBAC, and enterprise identity providers. Design and enforce application and API security standards, including SSL/TLS, encryption, secrets management, certificate management, secure configuration, and least-privilege access

Implement secure communication between cloud services, databases, APIs, external systems, AI services, and front-end applications. Design cloud networking and infrastructure components including application hosting, databases, storage, identity, networking, firewalls, gateways, load balancing, monitoring, logging, and availability strategies. Develop integration architectures for internal systems, third-party applications, vendor APIs, and enterprise platforms.

Design data pipelines, ETL processes, data transformation services, and system-to-system integrations where required. Establish logging, monitoring, auditing, alerting, and observability standards across backend services and cloud infrastructure. Design scalable architectures capable of supporting increasing users, transaction volumes, data volumes, integrations, AI workloads, and application workloads.

Implement caching, asynchronous processing, queues, background services, and other distributed architecture patterns when appropriate. Develop and maintain CI/CD pipelines and infrastructure deployment processes. Work closely with front-end developers to define API requirements, data contracts, authentication flows, AI service interactions, and integration standards.

Design and implement AI workflow architectures that enable Large Language Models to perform complex business functions by defining process sequences, system instructions, prompt strategies, retrieval mechanisms, examples, evaluation methods, tool interactions, and orchestration workflows. Architect AI systems capable of incorporating enterprise knowledge and business processes through structured process definitions, contextual examples, retrieval, tool use, and iterative refinement so that AI can reliably execute operational business tasks. Design Retrieval-Augmented Generation (RAG) architectures that securely retrieve relevant enterprise information from databases, documents, APIs, vector stores, and other approved business data sources.

Design secure AI integration patterns that control how LLMs access enterprise databases, APIs, internal systems, and sensitive business information. Establish AI evaluation, testing, monitoring, and quality standards to measure accuracy, reliability, consistency, security, and effectiveness of AI-powered workflows. Collaborate with business stakeholders and development teams to translate application requirements and business processes into technical and AI architectures.

Evaluate technical risks, scalability requirements, security concerns, infrastructure costs, AI usage costs, and architectural tradeoffs. Conduct architecture and code reviews and establish backend, database, API, cloud, security, and AI development standards. Provide technical leadership and mentoring to developers working within the architecture.