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Data Engineer Jobs in Montgomery, AL (NOW HIRING)

TechFlow is seeking an experienced Database Engineer / Oracle Database Administrator (DBA) to ... Support ETL processes, data integration activities, and maintenance of database metadata and data ...

We are seeking a dedicated Data Center Repair Technician to join our infrastructure engineering team. This role is focused on the physical repair and maintenance of data center hardware, including ...

Support ETL processes, data integration activities, and maintenance of database metadata and data ... Engineering or related field. * Minimum 5 years of Oracle Database Administration experience ...

Support ETL processes, data integration activities, and maintenance of database metadata and data ... Engineering or related field. * Minimum 5 years of Oracle Database Administration experience ...

Support ETL processes, data integration activities, and maintenance of database metadata and data ... Engineering or related field. * Minimum 5 years of Oracle Database Administration experience ...

Support ETL processes, data integration activities, and maintenance of database metadata and data ... Engineering or related field. * Minimum 5 years of Oracle Database Administration experience ...

Our data centers are the backbone of the infrastructure that powers Meta's global platforms, and this role is central to keeping those systems running at peak reliability. As a Lead Building Engineer ...

Data Center Technician

Montgomery, AL ยท On-site

$21 - $25/hr

We are seeking a dedicated Data Center Technician to join our infrastructure engineering team. The ideal candidate will be responsible for the installation, service, maintenance, repair, and ...

Showing results 41-60

Data Engineer information

See Montgomery, AL salary details

$44K

$128.3K

$175.6K

How much do data engineer jobs pay per year?

As of Aug 20, 2026, the average yearly pay for data engineer in Montgomery, AL is $128,317.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,300.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a data engineer?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

What are the key skills and qualifications needed to thrive as a data engineer, and why are they important?

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What does a data engineer do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

How do data engineers typically collaborate with data scientists and analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior-level role that requires experience with programming, databases, and data pipeline tools. Entry-level positions may be available for those with relevant internships or strong foundational skills, but most data engineering roles demand several years of experience or advanced knowledge of tools like SQL, Python, and cloud platforms.

What is the role of a data engineer?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, process, and store large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible and reliable for analysis and decision-making.

What are the most commonly searched types of Data Engineer jobs in Montgomery, AL?

The most popular types of Data Engineer jobs in Montgomery, AL are:

What are popular job titles related to Data Engineer jobs in Montgomery, AL?

For Data Engineer jobs in Montgomery, AL, the most frequently searched job titles are:

What job categories do people searching Data Engineer jobs in Montgomery, AL look for?

The top searched job categories for Data Engineer jobs in Montgomery, AL are:

What cities near Montgomery, AL are hiring for Data Engineer jobs?

Cities near Montgomery, AL with the most Data Engineer job openings:

Infographic showing various Data Engineer job openings in Montgomery, AL as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $128,317 per year, or $61.7 per hour.

Cloud Solutions Architect / Database Engineer / AI Platform Architect

ABCO MAINTENANCE INC. (BIC# 1854)

Montgomery, AL โ€ข On-site

$150K - $180K/yr

Full-time

Posted 13 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.