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Data Optimizer Jobs in Georgia (NOW HIRING)

nLeague Services Inc

Data Scientist

Atlanta, GA · On-site

Model Development and Optimization: Design, build, and refine predictive models and algorithms to enhance decision-making and drive business value. * Data Infrastructure Management: Maintain and ...

CYNET SYSTEMS

Data Engineer

Columbus, GA · On-site

$48 - $53/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Experience with Query Performance Tuning and Optimization. Experience with Bitbucket/Git Version ... Build scalable data processing workflows using Python and PySpark. Develop and optimize SQL/PLSQL ...

CYNET SYSTEMS

Data Engineer

Columbus, GA · On-site

$48 - $53/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Experience with Query Performance Tuning and Optimization. * Experience with Bitbucket/Git Version ... Build scalable data processing workflows using Python and PySpark. * Develop and optimize SQL/PLSQL ...

Cynet Systems

Data Engineer

Columbus, GA · On-site

$48 - $53/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Experience with Query Performance Tuning and Optimization. * Experience with Bitbucket/Git Version ... Build scalable data processing workflows using Python and PySpark. * Develop and optimize SQL/PLSQL ...

Mindlance

Data Engineer 4

Atlanta, GA · On-site

$110K - $132K/yr

The role involves building and optimizing data pipelines, supporting analytics, and leveraging AI tools to enhance data engineering tasks. Responsibilities : • Building, operating, and optimizing ...

Hexaware Technologies, Inc

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Solid SQL SQL skills and familiarity with data modeling and query optimization * Experience with ETL best practices, data quality checks, and monitoring/alerting * Familiarity with version control ...

4pconsultinginc

Data Engineer III

Atlanta, GA · On-site

$110K - $132K/yr

The ideal candidate will have deep experience in data transformation, SQL optimization, Data Lakehouse architectures, and distributed processing systems. Proficiency in Databricks, Azure, Spark, Hive ...

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Data Optimizer information

What is a data optimizer?

Data Optimizers are professionals who analyze, refine, and improve how data is collected, stored, processed, and utilized within an organization. They work to enhance data quality, streamline workflows, and ensure that businesses can make the most effective use of their data assets. By implementing best practices and leveraging technology, Data Optimizers help organizations gain actionable insights, reduce inefficiencies, and support better decision-making. Their role often involves working closely with data engineers, analysts, and business stakeholders to optimize data systems and processes.

How does a data optimizer typically collaborate with data engineers and analysts within a project team?

A Data Optimizer works closely with data engineers to ensure data pipelines are efficient, scalable, and aligned with organizational goals. They often review current data structures, identify inefficiencies, and propose enhancements that streamline data flow and improve performance. Collaboration with analysts is also key, as Data Optimizers help ensure data quality and availability for analytical tasks, often translating business needs into technical improvements. This role requires strong communication skills and the ability to bridge the gap between technical teams and business stakeholders.

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

To thrive as a Data Optimizer, you need strong analytical skills, a solid understanding of data management principles, and experience with data cleaning and transformation, typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools like SQL, Python, data visualization software, and data warehousing systems is common, and certifications in data analytics or database management can be advantageous. Attention to detail, problem-solving abilities, and effective communication are crucial soft skills for interpreting data and collaborating with cross-functional teams. These competencies ensure data integrity, facilitate informed decision-making, and drive organizational efficiency through optimized data processes.

What is the difference between Data Optimizer vs Data Analyst?

AspectData OptimizerData Analyst
CredentialsTypically requires certifications in data management, SQL, or data analysis toolsOften holds degrees in statistics, mathematics, or related fields
Work EnvironmentFocuses on data quality, efficiency, and process improvement within data systemsAnalyzes data sets to identify trends and generate reports for decision-making
Employer & Industry UsageUsed in industries emphasizing data infrastructure and optimizationCommon across various industries for business insights and reporting

While both roles work with data, Data Optimizers focus on enhancing data quality and system efficiency, whereas Data Analysts interpret data to support business decisions. Understanding these differences helps organizations assign the right skills to each role.

What cities in Georgia are hiring for Data Optimizer jobs?

Cities in Georgia with the most Data Optimizer job openings:

Data Optimizer jobs near you
Infographic showing various Data Optimizer job openings in Georgia as of June 2026, with employment types broken down into 11% As Needed, and 89% Part Time. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Data Architect C2C requirements Alpharetta, GA

Tech Mirrors

Alpharetta, GA • On-site

$110 - $165/hr

Other

Posted 5 days ago

Job description

Role: Data Architect

Location: Alpharetta, GA

Job Description: Database Optimization, Data Modeling, Database Consolidation, Oracle to SQL Server Migration, Client Problem Statement

The organization has multiple databases with performance, scalability, and maintenance challenges. They need an expert who can optimize existing Microsoft SQL Server databases, redesign data models where required, merge databases from different applications, and support migration from Oracle to SQL Server while minimizing business disruption.

What They Are Looking ForDatabase Optimization
  • Query tuning and execution plan analysis
  • Index optimization (clustered, non-clustered, filtered indexes)
  • Statistics maintenance
  • Partitioning strategies
  • Performance bottleneck identification
  • Deadlock analysis
  • TempDB optimization
  • Storage optimization
  • SQL profiling and monitoring
Data Modeling
  • Logical data model design
  • Physical data model design
  • ER modeling
  • Normalization and denormalization
  • Master Data Management (MDM)
  • Canonical data modeling
  • Data governance
  • Database Consolidation
Database Consolidation
  • Schema comparison
  • Data mapping
  • Duplicate entity resolution
  • Common data model creation
  • Data standardization
  • Data quality assessment
  • Cross-application relationship management
Oracle to SQL Server Migration
  • Oracle schema assessment
  • SQL dialect conversion
  • PL/SQL to T-SQL conversion
  • Stored procedure migration
  • Trigger migration
  • Function conversion
  • Performance benchmarking
  • Data validation and reconciliation
Skills RequiredTechnical Skills
  • MS SQL Server
  • Oracle Database
  • T-SQL
  • PL/SQL
  • SSIS
  • SSMS
  • Azure SQL
  • Data Modeling Tools (ERWin, ER Studio)
  • Query Store
  • SQL Profiler
Architecture Skills
  • Data Architecture
  • Database Modernization
  • Data Governance
  • Data Migration Strategy
  • Performance Engineering
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