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Data Solutions Developer Jobs in Tennessee (NOW HIRING)

Data Engineer

Knoxville, TN · Hybrid

$109K - $131K/yr

Join a hybrid Data Engineer opportunity focused on building and improving modern big data solutions for ingestion, integration, and transformation. This role supports impactful data initiatives and ...

New

Senior Data Engineer (Remote)

Nashville, TN · On-site

$110K - $132K/yr

Design and build end‑to‑end data solutions on Azure. * Develop lakehouse architectures using ... Hands‑on Azure DevOps (branching, PRs, testing, pipelines). * Experience with data quality ...

Senior Data Engineer

Nashville, TN · On-site

$102K - $139K/yr

Design, develop, test, validate, document, and maintain scalable data engineering solutions and ... self-service analytics platforms. * Build high-quality SQL-based data pipelines, curated datasets ...

Sr. Data Engineer - CX Analytics

Chattanooga, TN · Remote

$104K - $125K/yr

Here, we work to provide the employee benefits and service solutions that enable employees at our ... Experience in DevOps best practice including CI/CD, process automation and optimization. * Data ...

Showing results 21-40

Data Solutions Developer information

How does a Data Solutions Developer typically collaborate with data analysts and business stakeholders?

As a Data Solutions Developer, collaboration with data analysts and business stakeholders is integral to delivering effective data-driven solutions. You will frequently engage in requirements-gathering sessions to understand business needs, translate those needs into technical specifications, and iterate on data models or pipelines based on feedback. Regular meetings and clear communication are essential to ensure the solutions you develop align with business goals and analytics objectives. Additionally, you may provide technical guidance to analysts on data access or usage and help stakeholders interpret results from the systems you build.

What is the difference between Data Solutions Developer vs Data Engineer?

AspectData Solutions DeveloperData Engineer
Primary FocusDesigning and developing data solutions and applicationsBuilding and maintaining data pipelines and infrastructure
Skills & CertificationsSQL, programming, data modeling, cloud platformsETL, database systems, cloud services, scripting
Work EnvironmentCollaborates with data analysts, developers, and business teamsWorks on data architecture, infrastructure, and backend systems
Industry UsageUsed across industries for data application developmentPrimarily in data-heavy sectors like tech, finance, and healthcare

While both roles involve working with data, Data Solutions Developers focus on creating data applications and solutions, whereas Data Engineers concentrate on building the data infrastructure and pipelines. Understanding these differences helps in choosing the right career path or job role.

What are the key skills and qualifications needed to thrive as a Data Solutions Developer?

To thrive as a Data Solutions Developer, you need strong programming skills (such as Python, SQL, or Java), a solid understanding of data architecture, and typically a degree in computer science or a related field. Familiarity with data warehousing tools, ETL processes, cloud platforms (like AWS or Azure), and certifications such as Microsoft Certified: Azure Data Engineer Associate are highly valued. Analytical thinking, problem-solving, and effective communication help you collaborate with stakeholders and translate business requirements into technical solutions. These skills ensure the delivery of robust, scalable data solutions that drive informed decision-making and business success.

What does a data solutions developer do?

A data solutions developer designs, develops, and implements data management and analytics solutions to help organizations process and interpret large datasets. They often work with programming languages like SQL, Python, or Java, and use tools such as data warehouses and ETL processes to create efficient data workflows. Their role involves collaborating with stakeholders to understand data needs and ensuring solutions are scalable and secure.
Infographic showing various Data Solutions Developer job openings in Tennessee as of August 2026, with employment types broken down into 83% Full Time, 10% Part Time, and 7% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution.

Cloud Solutions Architect / Database Engineer / AI Platform Architect

ABCO MAINTENANCE INC. (BIC# 1854)

Nashville, TN

$150K - $180K/yr

Full-time

Posted 5 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.