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Data Engineer Jobs in Montgomery, AL (NOW HIRING)

Bespoke Labs

Data Engineer

Montgomery, AL · On-site

$113K - $136K/yr

Must-Have Skills 3+ years of data engineering experience -- pipelines, ETL, data modeling in production or research settings Strong Python proficiency (numpy, pandas, Parquet, HDF5 are daily tools ...

Bespoke Labs

Data Engineer

Montgomery, AL

$113K - $136K/yr

Must-Have Skills 3+ years of data engineering experience -- pipelines, ETL, data modeling in production or research settings Strong Python proficiency (numpy, pandas, Parquet, HDF5 are daily tools ...

vTech Solution

Data Quality Engineer

Montgomery, AL · On-site

$113K - $136K/yr

Data Quality Engineer Duration : 03 months (Possibility of extension) Location : Montgomery, AL - 36130 (Onsite) Interview: Video or In person Based on Location A Data Quality Engineer, strong data ...

Meta

Data Center Capacity Engineer

Montgomery, AL

$111K/yr

Meta is seeking a Data Center Capacity Engineer to help ensure our global data center infrastructure can meet the demands of billions of users across Meta's family of apps and services. In this role ...

Neptune

Software Engineer (BI)

Tallassee, AL · On-site

We make data actionable using effective software and measurement systems that are interconnected by ... Software Engineer (BI) Position Summary As a Business Intelligence Software Engineer, you will ...

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All JobsData Engineer JobsData Engineer Jobs in Montgomery, AL

Data Engineer information

See Montgomery, AL salary details

$44K

$128.3K

$175.5K

How much do data engineer jobs pay per year?

As of Aug 4, 2026, the average yearly pay for data engineer in Montgomery, AL is $128,260.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,200.00 and $136,000.00 per year, depending on experience, location, and employer.

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.

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.

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.

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.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior-level role that requires experience with programming, databases, and data pipelines. 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 and proficiency with tools like SQL, Python, and cloud platforms.
More about Data Engineer jobs
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:
Data Engineer jobs near you
Infographic showing various Data Engineer job openings in Montgomery, AL as of July 2026, with employment types broken down into 72% Full Time, and 28% Contract. Highlights an 100% In-person job distribution, with an average salary of $128,260 per year, or $61.7 per hour.

Data Engineer

Bespoke Labs

Montgomery, AL • On-site

$113K - $136K/yr

Full-time

Re-posted 17 days ago

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of data engineering experience — pipelines, ETL, data modeling in production or research settings

Strong Python proficiency (numpy, pandas, Parquet, HDF5 are daily tools)

Familiarity with at least one RL framework (Gymnasium / OpenAI Gym, dm_env, or equivalent) and working knowledge of RL environment structure — observation/action spaces, reward signals, episode logic

Experience with data versioning and experiment tracking (DVC, MLflow, W&B, or similar)

Comfortable with Docker and cloud infrastructure (AWS or GCP)

Solid grasp of ML storage formats: Parquet, HDF5, JSON Lines

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