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Data Engineer Jobs in Montgomery, AL (NOW HIRING)

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 ...

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See Montgomery, AL salary details

$44K

$128.3K

$175.6K

How much do data engineer jobs pay per year?

As of Aug 27, 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.
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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 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 August 2026, with employment types broken down into 73% Full Time, 9% Temporary, and 18% Contract. Highlights an 100% In-person job distribution, with an average salary of $128,317 per year, or $61.7 per hour.

Data Quality Engineer

Montgomery, AL • On-site

vTech Solution
IT Services • 51 - 200 employees
Learn more about vTech Solutionexternal

$113K - $136K/yr

Contractor

Re-posted yesterday

Job description

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

Job Description:
A Data Quality Engineer, strong data analyst with deep technical skills in SQL, Purview, Data Pipelines and Data Modeling, plus experience in cloud data environments, automated testing, and collaboration with analytics and engineering teams. Ensures data is not only clean but also ready to support advanced analytics and AI applications

Data Quality Engineer & Analytics Skills:

  • Core Technical Skills Must Be Able To Navigate An Environment With Low\No Data Maturity
  • Data Profiling & Cleansing: Analyze data to identify anomalies, duplicates, outliers, and missing values; apply cleansing techniques to improve data integrity.
  • SQL Proficiency: Write complex queries to validate data accuracy, perform transformations, and generate reports. (SSIS - ETL\ELT)
  • Python & Other Languages: Python is widely used for automation, data validation, and integration with analytics pipelines; SQL is essential for querying and reporting.
  • Data Modeling & Warehousing: Understand ETL/ELT processes, data warehouse/lake/lakehouse architectures, and data modeling principles.
  • Cloud & Modern Data Stack: Experience with cloud platforms (AWS, GCP, Azure), modern data warehouses (Snowflake, BigQuery), and tools like Spark, Kafka/Kinesis, Hadoop, or S3.
  • Data Testing & Observability: Design and deploy automated data testing at scale; use observability platforms for real-time monitoring.

Analytics & Data Science Skills:

  • Data Quality Standards & Metrics: Define and enforce data quality benchmarks; measure completeness, accuracy, timeliness, and consistency.
  • Root Cause Analysis: Identify why data issues occur (ETL bugs, user input errors, system failures) and implement fixes.
  • Collaboration with Data Scientists: Work with ML/data science teams to ensure training data is clean and reliable.
  • Statistical & Trend Analysis: Interpret patterns in large datasets to inform quality improvements.

Soft & Communication Skills:

  • Stakeholder Engagement: Gather requirements from business, engineering, and analytics teams; advocate for data quality across the organization.
  • Problem-Solving & Attention to Detail: Spot and resolve data issues efficiently; maintain high precision in validation.
  • Documentation: Record quality issues, processes, and improvements for transparency and compliance.

Tools & Platforms:

  • Query & Analysis: SQL, Python, Spark, Kafka/Kinesis, Hadoop, S3.
  • Data Quality Tools: Data profiling tools (MS Purview), validation scripts, observability platforms.
  • Collaboration: Jira, Snowflake, or other data governance platforms.

Required Skills

  • Strong experience working in low or immature data environments, establishing data quality processes from scratch (8-10 Years)
  • Advanced SQL expertise for complex querying, data validation, and transformation (8-10 Years)
  • Hands-on experience with ETL/ELT pipelines (e.g., SSIS or similar tools) (8-10 Years)
  • Proficiency in Python for data automation, validation, and pipeline integration (5-8 Years)
  • Experience with data profiling and cleansing (anomalies, duplicates, outliers, missing values) (8-10 Years)
  • Solid understanding of data modeling and data warehouse/lake/lakehouse architectures (8-10 Years)
  • Experience implementing data quality frameworks and metrics (accuracy, completeness, timeliness, consistency) (8-10 Years)
  • Experience with cloud data platforms (AWS, Azure, or GCP) and modern data warehouses (e.g., Snowflake, BigQuery) (5-8 Years)
  • Required Tools & Platforms: (8-10 Years) Query & Analysis: SQL, Python, Spark, Kafka/Kinesis, Hadoop, S3. Data Quality Tools: Data profiling tools (MS Purview), validation scripts, observability platforms. Collaboration: Jira, Snowflake, or other data governance platforms.
  • Bachelor's Degree

Preferred Skills

  • Knowledge of DAMA-DMBoK, DCAM, MDM concepts, and governance frameworks. (8-10 Years)
  • Experience with Microsoft Purview, Fabric, MS Power BI, and Key Vault (5-8 Years)
  • Familiarity with AI/ML data readiness and feature-store-aligned data structuring. (5-8 Years)
  • Cloud data engineering exposure (Azure, Databricks, GCP). (5-8 Years)
  • Master’s degree preferred.
  • DAMA CDMP (Associate/Practitioner) · EDM Council DCAM · ASQ Data Quality Credential · Collibra Data Steward Certification · Certified Data Steward (eLearningCurve) · Cloud/AI certifications (Azure, Databricks, Google)

vTech Solution Inc. is a Managed IT Services firm headquartered in Washington, DC. They specialize in a range of services including cloud computing, managed network security, and cybersecurity. Their primary focus is on providing human-centered IT solutions for government and business sectors, including federal, state, local, and education (SLED) groups, as well as commercial organizations.

vTech Solution offers services such as:

  • Managed Security Services: Implementing zero-trust security frameworks to prevent cyber threats in real-time.
  • Multi-cloud Management Services: Helping businesses digitally transform with smart cloud technologies.
  • Infrastructure Managed Services: Creating resilient and secure infrastructure management.
  • Professional Services: Providing expertise for mission-critical programs.
  • Productivity and Communications: Ensuring secure and confident business connectivity from anywhere
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About vTech Solution

Sourced by ZipRecruiter

vTech is a Managed IT Services firm based out of Washington DC with a primary focus on Cloud Computing and Managed Network Security.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Washington, DC, US

Year founded

2006

Social media

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