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Data Quality Jobs in Alabama (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 ...

Kemper

Data Quality Engineer

Birmingham, AL · Remote

$107K - $128K/yr

Kemper is seeking a Data Quality Engineer specializing in Data Testing and Quality Engineering to design, implement, and optimize enterprise data validation frameworks that ensure the accuracy ...

Daimler

Quality and Data Engineer

Vance, AL

$64K - $83K/yr

Under general supervision, this position bridges data engineering and automotive quality to enable data-driven decision-making. The role focuses primarily on designing, building, and maintaining data ...

Deckers

Define data quality metrics, thresholds, and monitoring approaches, driving accountability through transparent scorecards and remediation processes * Lead governance operationalization by embedding ...

PNC Bank

Data Manager

Birmingham, AL

Data Quality Define and implement data quality standards and metrics. Conduct regular data quality assessments and audits, focusing on the accuracy and integrity of sensitive financial and personal ...

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How much do data quality jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for data quality in Alabama is $37.56, according to ZipRecruiter salary data. Most workers in this role earn between $25.29 and $49.23 per hour, depending on experience, location, and employer.

Is data quality a good career?

Data quality is a valuable career path involving ensuring the accuracy, consistency, and reliability of data within organizations. Professionals in this field often work with data management tools, perform audits, and may pursue certifications like Certified Data Management Professional (CDMP). It offers opportunities across industries such as finance, healthcare, and technology with steady demand for skilled data quality specialists.

Is 40 too late for data science?

Data science is a field open to professionals of all ages, and starting at 40 is not too late. Success depends on acquiring relevant skills such as programming, statistics, and tools like Python or R, along with practical experience. Many individuals transition into data science later in their careers and find opportunities based on their expertise and continuous learning.

What is the highest paying data job?

The highest paying data jobs often include Data Science Director, Chief Data Officer, or Data Engineering Manager roles, which can earn six-figure salaries or higher depending on experience, industry, and location. These positions typically require advanced skills in data analysis, machine learning, and leadership, along with relevant certifications or degrees.

What are the key skills and qualifications needed to thrive in the Data Quality position, and why are they important?

To thrive in a Data Quality role, you need expertise in data analysis, attention to detail, knowledge of data governance, and often a bachelor's degree in a related field such as computer science or information systems. Familiarity with tools like SQL, data profiling software, and data quality management platforms, as well as certifications like CDMP (Certified Data Management Professional), is highly valued. Strong problem-solving abilities, effective communication, and a collaborative mindset help professionals excel in this position. These skills are crucial for ensuring accurate, reliable data that supports business decision-making and overall organizational efficiency.

What is a Data Quality job?

A Data Quality job involves ensuring that data is accurate, consistent, and reliable for business use. Professionals in this role develop and enforce data quality standards, identify and resolve data discrepancies, and implement processes for data validation and cleansing. They often work with databases, data governance frameworks, and analytics teams to maintain high-quality data. This role is essential for organizations relying on data-driven decisions, as poor data quality can lead to incorrect insights and inefficiencies.

What are the typical challenges faced by someone working in a Data Quality role?

Professionals in Data Quality roles often encounter challenges such as identifying inconsistent data sources, addressing missing or inaccurate data, and maintaining data standards as systems and business requirements evolve. Working closely with IT, data analysts, and business stakeholders, Data Quality specialists must resolve data discrepancies while balancing the need for accuracy with project deadlines. These challenges require excellent analytical and troubleshooting skills, as well as the ability to communicate data issues clearly across teams. Overcoming these hurdles is key to ensuring data-driven decisions are based on trustworthy information.

What is a data quality job?

A data quality job involves ensuring the accuracy, completeness, consistency, and reliability of data within an organization. Professionals in this role often use tools like data profiling and validation software, and may hold certifications such as Certified Data Management Professional (CDMP). The work typically requires attention to detail and understanding of data governance standards.
What are the most commonly searched types of Data Quality jobs in Alabama? The most popular types of Data Quality jobs in Alabama are:
What are popular job titles related to Data Quality jobs in Alabama? For Data Quality jobs in Alabama, the most frequently searched job titles are:
What job categories do people searching Data Quality jobs in Alabama look for? The top searched job categories for Data Quality jobs in Alabama are:
Data Quality jobs near you
Infographic showing various Data Quality job openings in Alabama as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 18% Part Time, and 6% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $78,119 per year, or $37.6 per hour.
Data Quality Engineer

Data Quality Engineer

vTech Solution

Montgomery, AL • On-site

$113K - $136K/yr

Contractor

Posted 29 days ago

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

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