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Data Analytics Engineer Jobs in Alabama (NOW HIRING)

Data, Analytics & AI Engineer

Birmingham, AL

$107K - $128K/yr

Data, Analytics & AI Engineer Help Build the Future of Data, Analytics & AI Are you passionate about data engineering, analytics, and artificial intelligence? Do you love solving complex business ...

This position is responsible for developing advanced analytics solutions, integrating data from multiple sources, and presenting actionable insights to business and engineering leaders. The ideal ...

Data Analytics Analyst 1

Birmingham, AL · On-site

$27.75 - $29.75/hr

Gather equipment-related information from engineering documents, project teams, plant personnel ... Data Analytics & Technical Analysis * Perform daily analysis of technical and operational data.

Job Title DATA ENGINEER/DATA ANALYST Location Huntsville, AL US (Primary) Category Engineering Job ... advanced analytics, and programmatic domains. As an employee-owned SDVOSB headquartered in ...

Showing results 21-40

Data Analytics Engineer information

See Alabama salary details

$40.3K

$117.6K

$160.9K

How much do data analytics engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for data analytics engineer in Alabama is $117,573.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,800.00 and $124,600.00 per year, depending on experience, location, and employer.

How do data analytics engineers typically collaborate with data scientists and business stakeholders on projects?

Data Analytics Engineers play a crucial role in bridging the gap between raw data and actionable insights by building, optimizing, and maintaining data pipelines. They often work closely with data scientists to ensure data is clean, accessible, and structured for advanced analytics or machine learning models. Additionally, they collaborate with business stakeholders to understand reporting requirements and ensure that data solutions align with organizational objectives. Regular communication and cross-functional teamwork are essential aspects of this role, as engineers must translate business needs into technical specifications and deliver reliable data products.

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

To thrive as a Data Analytics Engineer, you need strong proficiency in data modeling, SQL, and statistical analysis, typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools such as Python, R, Apache Spark, Tableau, and cloud data platforms like AWS or Google BigQuery is essential, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you translate data insights into actionable business solutions. These skills and qualities are crucial for designing robust data pipelines and enabling data-driven decision-making across organizations.

What is the difference between Data Analytics Engineer vs Data Scientist?

AspectData Analytics EngineerData Scientist
CredentialsBachelor's or master's in CS, Data Science, or related fields; certifications like Google Data AnalyticsBachelor's or master's in CS, Statistics, or related fields; certifications like Certified Data Scientist
Work EnvironmentFocus on building data pipelines, dashboards, and analytics toolsFocus on statistical modeling, machine learning, and data exploration
Employer & Industry UsageUsed across tech, finance, healthcare for data infrastructure and analyticsCommon in research, product development, and advanced analytics teams

While both roles work with data, Data Analytics Engineers primarily develop data infrastructure and tools for analysis, whereas Data Scientists focus on statistical modeling and machine learning to generate insights. They often collaborate but have distinct technical focuses.

What does a data analytics engineer do?

A data analytics engineer designs, builds, and maintains data pipelines and infrastructure to collect, process, and analyze large datasets. They use tools like SQL, Python, and cloud platforms to enable data-driven decision-making and often collaborate with data scientists and business teams to develop insights and reports.

What are the most commonly searched types of Data Analytics Engineer jobs in Alabama?

The most popular types of Data Analytics Engineer jobs in Alabama are:

Infographic showing various Data Analytics Engineer job openings in Alabama as of August 2026, with employment types broken down into 76% Full Time, and 24% Contract. Highlights an 100% In-person job distribution, with an average salary of $117,573 per year, or $56.5 per hour.

Data, Analytics & AI Engineer

Deploy

Birmingham, AL

$107K - $128K/yr

Full-time

Re-posted 15 days ago


Job description

Data, Analytics & AI Engineer

Help Build the Future of Data, Analytics & AI

Are you passionate about data engineering, analytics, and artificial intelligence?

Do you love solving complex business problems while working with cutting-edge technology?

If so, this is an opportunity to make a real impact.

Our client is looking for a Data, Analytics & AI Engineer to help design, build, and evolve a modern enterprise data platform.

This is a highly visible, hands-on role where you'll work at the intersection of data engineering, business intelligence, analytics, and AI, creating intelligent solutions that drive smarter decisions and automate business processes across the organization.

You'll help build scalable data pipelines, develop powerful analytics, and create AI-enabled and agentic workflows that improve efficiency, generate insights, and transform how the business operates. You'll also play a key role in the organization's exciting transition to Microsoft Fabric, helping shape the future of its data ecosystem.

If you're someone who enjoys building things, learning new technologies, and bringing AI into real-world business applications, we'd love to talk to you.

What You'll Do

Build Modern Data Platforms

Design, build, and maintain scalable data pipelines using Azure Data Factory and Boomi.

Integrate data from ERP, EHS, operational, and enterprise systems.

Develop and manage curated data models in Azure SQL while helping migrate to Microsoft Fabric Lakehouse and Warehouse architectures.

Ensure high levels of data quality, performance, governance, and reliability.

Help establish best practices and architecture standards for the next generation data platform.

Deliver Powerful Analytics

Build interactive dashboards, semantic models, and reports using Power BI.

Partner with business leaders to translate business questions into actionable KPIs and analytics.

Enable self-service reporting through well-designed datasets and documentation.

Turn raw data into meaningful business insights.

Drive AI Innovation

Design, prototype, and deploy AI and Machine Learning solutions.

Build intelligent workflows that automate multi-step business processes using AI and agentic technologies.

Leverage Azure AI services and Microsoft Fabric capabilities including notebooks, machine learning, and real-time analytics.

Champion responsible AI adoption across the organization.

Identify opportunities where AI can improve forecasting, anomaly detection,

classification, automation, and decision-making.

Collaborate Across the Business

Partner with IT, Security, DevOps, and business leaders to deliver secure, scalable solutions.

Work closely with cross-functional teams and affiliate companies on strategic initiatives.

Manage projects with measurable business outcomes and clear success metrics.

Innovate Continuously

Evaluate emerging technologies in data, analytics, and AI.

Recommend improvements that create measurable business value.

Foster a culture of innovation, experimentation, and data-driven decision making.

What We're Looking For

Required Qualifications

Bachelor's degree (or higher) in Computer Science, Data Science, Engineering,

Statistics, Applied Mathematics, or a related field.

Strong experience building enterprise data pipelines using Azure Data Factory, Boomi, or similar integration tools.

Excellent SQL skills with experience designing relational data models.

Experience with Azure SQL Database or similar database technologies.

Hands-on experience building Power BI semantic models, dashboards, and reports.

Programming experience with Python, including notebooks and data engineering workflows.

Practical experience applying AI and Machine Learning to solve real business challenges.

Strong analytical and problem-solving skills.

Ability to communicate technical concepts to both technical and non-technical audiences.

Curious, self-motivated, and excited about learning new technologies.

Bonus Points If You Have

Experience with Microsoft Fabric, including Lakehouse, Warehouse, Notebooks,

Real-Time Analytics, and AI workloads.

Familiarity with agentic AI, workflow orchestration, or intelligent automation platforms.

Experience supporting enterprise data platforms in regulated or security-conscious environments.

Knowledge of modern data architecture, including ELT, semantic layers, governance, and data lineage.

Experience working in large, multi-company, or distributed enterprise environments.

A customer-first mindset with the ability to build strong relationships across the business.

Why You'll Love This Opportunity

Work on meaningful projects using the latest AI and analytics technologies.

Help shape the future of a rapidly evolving enterprise data platform.

Play a key role in an organization's Microsoft Fabric transformation.

Collaborate with talented business and technology leaders.

Build solutions that directly influence strategic business decisions.

Be part of a culture that embraces innovation, experimentation, and continuous learning.

If you're excited about building modern data platforms, leveraging AI to solve real business problems, and making a measurable impact, we'd love to hear from you.