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Data Analyst Python Sql Jobs in Oneonta, AL (NOW HIRING)

Data, Analytics & AI Engineer

Birmingham, AL

$107K - $128K/yr

Develop and manage curated data models in Azure SQL while helping migrate to Microsoft Fabric ... Programming experience with Python, including notebooks and data engineering workflows. Practical ...

Data Engineer III

Birmingham, AL · On-site

$107K - $128K/yr

Work with MSBI tools (SSIS, SSAS), Informatica, Oracle Golden Gate AI/ML & Advanced Analytics Support * Support statistical models and AI/ML solutions using Python and/or R * Prepare data pipelines ...

... SQL, Python, PowerShell, or automation tools. * Familiarity with GIS, mapping, or geospatial data ... Key Skills Data analysis, reporting, system monitoring, Excel, process improvement, documentation ...

Strong proficiency in SQL with experience developing complex queries and data rules Hands-on experience with Python for data analysis or automation Experience working in AWS-based data environments ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary ... SQL - Experience with Docker and containerized deployments - Skilled in AI techniques enhancing ...

SQL Tutor

Birmingham, AL · Remote

$18 - $40/hr

... data analysis, database administration, and software development careers. * Conceptual Teaching ... Familiar with SQL curricula and common challenges such as understanding join types, writing complex ...

... SQL and data visualization tools - Experience in designing advanced analytics solutions - Coaching and collaborating with team members Travel Requirements Up to 80% Job Posting End Date The salary ...

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Data Analyst Python Sql information

See Oneonta, AL salary details

$27.2K

$66.1K

$108.8K

How much do data analyst python sql jobs pay per year?

As of Jul 14, 2026, the average yearly pay for data analyst python sql in Oneonta, AL is $66,083.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,000.00 and $77,600.00 per year, depending on experience, location, and employer.

Is Python and SQL enough for a data analyst?

For a data analyst, proficiency in Python and SQL is fundamental for data manipulation, analysis, and querying databases. However, additional skills such as data visualization, statistical knowledge, and familiarity with tools like Excel or BI platforms are often required to perform comprehensive analysis and communicate insights effectively.

What jobs can you get with SQL and Python?

Data analysts, data scientists, and business intelligence analysts commonly use SQL and Python to extract, analyze, and visualize data. These skills are essential for roles involving data management, reporting, and automation, often requiring knowledge of databases, statistical analysis, and data visualization tools.

How does a Data Analyst using Python and SQL typically collaborate with other departments within an organization?

Data Analysts proficient in Python and SQL frequently work alongside teams such as marketing, product development, finance, and operations. They gather requirements from stakeholders, translate business questions into data queries, and present actionable insights through dashboards or reports. Regular meetings and clear communication are essential to ensure that data solutions align with business goals, and Data Analysts often act as a bridge between technical data teams and non-technical decision makers. This collaborative environment helps drive data-informed decisions across the organization.

What are Data Analyst Python SQL jobs?

Data Analyst Python SQL jobs involve analyzing and interpreting data to help organizations make informed business decisions. These professionals use Python for data manipulation, automation, and visualization, and SQL for querying and managing data stored in relational databases. Typical tasks include data cleaning, building reports, extracting insights, and creating dashboards. Data Analysts often collaborate with other teams to understand data requirements and communicate findings through presentations or visualizations. Proficiency in both Python and SQL is essential for efficiently handling large data sets and solving complex analytical problems.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst; many professionals successfully transition into the field at various ages. Skills in Python, SQL, and data visualization tools are more important, and continuous learning can help overcome any age-related concerns. Employers value experience and analytical ability regardless of age.

What are the key skills and qualifications needed to thrive as a Data Analyst with Python and SQL, and why are they important?

To thrive as a Data Analyst specializing in Python and SQL, you need strong analytical skills, statistical knowledge, and proficiency in data manipulation, typically supported by a relevant degree or certification. Expertise in Python for data analysis, SQL for database querying, and experience with visualization tools like Tableau or Power BI are commonly expected. Attention to detail, problem-solving abilities, and effective communication are crucial soft skills for interpreting data and presenting actionable insights. These skills help ensure accurate analysis, impactful reporting, and informed decision-making within organizations.

Can Python and SQL work together?

Data analysts often use Python and SQL together to efficiently extract, manipulate, and analyze data. Python libraries like pandas and SQL connectors enable seamless integration, allowing analysts to automate workflows and perform complex data processing tasks within a single environment.

What is the difference between Data Analyst Python Sql vs Data Scientist?

AspectData Analyst Python SqlData Scientist
Required SkillsExcel, SQL, Python basics, data visualizationAdvanced Python, machine learning, statistical modeling
Work EnvironmentBusiness intelligence, reporting, dashboardsPredictive modeling, research, complex data analysis
Industry UsageFinance, marketing, retail, healthcareTech, finance, research institutions, startups

While Data Analysts with Python and SQL focus on interpreting data, creating reports, and visualizations, Data Scientists build predictive models and perform advanced statistical analysis. Both roles require Python and SQL skills, but Data Scientists typically have a stronger background in statistics and machine learning, making their work more research-oriented.

What cities near Oneonta, AL are hiring for Data Analyst Python Sql jobs? Cities near Oneonta, AL with the most Data Analyst Python Sql job openings:
Data, Analytics & AI Engineer

Data, Analytics & AI Engineer

Deploy

Birmingham, AL

$107K - $128K/yr

Full-time

Posted 8 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.