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Full Time Data Transformation Jobs (NOW HIRING)

Data Engineer - GCP

Atlanta, GA · On-site +1

$110K - $132K/yr

Data Transformation and Processing: * Develop data transformation processes using BigQuery, Apache ... This position is open to multiple engagement models, including Permanent/Full-Time, Contract, or ...

Data Engineer - GCP

Atlanta, GA · Remote

$117K - $140K/yr

Data Transformation and Processing: * Develop data transformation processes using BigQuery, Apache ... This position is open to multiple engagement models, including Permanent/Full-Time, Contract, or ...

Data Engineer - GCP

Atlanta, GA · On-site

$110K - $132K/yr

Data Transformation and Processing: * Develop data transformation processes using BigQuery, Apache ... This position is open to multiple engagement models, including Permanent/Full-Time, Contract, or ...

Data Engineer (Cycle)

Washington, DC · On-site

$85K - $100K/yr

Position Description America Votes is looking for a full-time Data Engineer for the 2026 cycle ... transformation, scripting, or working with APIs. * Experience using Git and other command line ...

Data Engineer (Cycle)

Washington, DC · Remote

$85K - $100K/yr

Position DescriptionAmerica Votes is looking for a full-time Data Engineer for the 2026 cycle. This ... transformation, scripting, or working with APIs.Experience using Git and other command line tools.

Position Description America Votes is looking for a full-time Data Engineer for the 2026 cycle ... transformation, scripting, or working with APIs. * Experience using Git and other command line ...

... full time, work experience as a data scientist solving complex problems. Must be highly experienced with data cleanups, data wrangling, data transformation, feature engineering, anomaly handling ...

... full time, work experience as a data scientist solving complex problems. Must be highly experienced with data cleanups, data wrangling, data transformation, feature engineering, anomaly handling ...

Summary/Objective Synensys is seeking a Data Scientist to support data integration, transformation ... Position Type/Expected Hours of Work This is a full-time position, generally performed during ...

New

Healthcare Data Engineer, Team Lead

$117K - $140K/yr

Job Type Full-time Description About Hart Hart is a leader in healthcare data accessibility and ... Design, build, and optimize SQL, Python, and Scala-based data transformation tools to support EHR ...

Enterprise Data Engineer

Chantilly, VA · On-site

$118K - $142K/yr

Implement data transformations, enrichment, and modeling workflows to ensure data quality and ... UNAVAILABLEEmployment Type: FULL_TIME

... Type Full-Time Career Level Experienced (Non-Manager) Education High School / GED Security ... data ingestion, transformation, modeling, validation, visualization, troubleshooting, and ...

Data Engineer

$117K - $140K/yr

Remote US Full time role Strict instruction don't submit consultants more than 8 to 12 years ... reliable data transformation and feature extraction pipelines * Collaborate with business and ...

This individual will have a chance to be a TGS full time employee. Top Skills' Details 10+ years ML ... A cornerstone of this roadmap is the acceleration of its data transformation and of the adoption of ...

Sr Data Engineer

Plantation, FL · Remote

$109K - $131K/yr

... SQL and complex data transformation logic to support analytics and reporting. 8)Monitor ... TYPICAL WORKING CONDITIONS • Full time remote/telework OTHER PHYSICAL REQUIREMENTS • Vision • ...

Showing results 21-40

Full Time Data Transformation information

What is a full time data transformation?

A Full Time Data Transformation job involves converting data from one format, structure, or system to another to ensure it is accurate, consistent, and usable for analysis or business processes. Professionals in this role typically work with large datasets, using tools and programming languages such as SQL, Python, or ETL (Extract, Transform, Load) platforms. They collaborate with data engineers, analysts, and business stakeholders to design workflows that streamline data integration, migration, or cleansing. This role is crucial in organizations that rely on data-driven decision-making, as it ensures high-quality, accessible data across systems.

What are the key skills and qualifications needed to thrive as a full time data transformation specialist?

To excel as a Full Time Data Transformation Specialist, you need strong analytical skills, proficiency in data modeling, and a relevant degree in computer science or a related field. Familiarity with ETL tools (such as Informatica, Talend, or Apache NiFi), SQL, and cloud data platforms is typically required, along with certifications in data management or analytics. Attention to detail, problem-solving abilities, and effective communication are crucial soft skills for translating business needs into technical solutions. These competencies ensure accurate, efficient data integration and enable organizations to make data-driven decisions.

What are some common challenges faced in a full time data transformation role, and how can I prepare for them?

In a Full Time Data Transformation role, you may encounter challenges such as handling inconsistent data sources, managing large volumes of data, and ensuring data quality throughout the transformation process. It’s important to develop strong problem-solving skills and familiarity with ETL tools, as well as a solid understanding of data governance and documentation practices. Collaborating effectively with data engineers, analysts, and business stakeholders is also crucial to ensure that transformed data meets organizational needs. Staying updated on best practices and being adaptable to evolving technologies will help you succeed and grow in this field.

What is the difference between Full Time Data Transformation vs Data Analyst?

AspectFull Time Data TransformationData Analyst
Required CredentialsBachelor's in CS, Data Science, or related field; experience with ETL toolsBachelor's in Statistics, Business, or related field; proficiency in Excel and SQL
Work EnvironmentData teams, IT departments, project-basedBusiness units, reporting teams, cross-functional
Industry UsageTech, finance, healthcare, retailFinance, marketing, consulting, healthcare
Common Search/ComparisonFull Time Data Transformation vs Data Analyst

Full Time Data Transformation roles focus on designing and implementing data pipelines, ETL processes, and data integration. Data Analysts primarily analyze data to generate reports and insights. While both roles require data skills, Data Transformation emphasizes data engineering tasks, whereas Data Analysts focus on data interpretation and visualization.

More about Full Time Data Transformation jobs

What cities are hiring for Full Time Data Transformation jobs?

Cities with the most Full Time Data Transformation job openings:

What are the most commonly searched types of Data Transformation jobs?

The most popular types of Data Transformation jobs are:

Infographic showing various Full Time Data Transformation job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Data Engineer - GCP

The Data Sherpas

Atlanta, GA • On-site, Remote

$110K - $132K/yr

Full-time

Medical, Dental, Vision

Re-posted 14 days ago


Job description

Who We Are:

We are a dynamic team focused on building innovative and scalable data solutions on Google Cloud Platform (GCP). Our Google Cloud Data Engineer will play a key role in designing, developing, and managing scalable data pipelines and data infrastructure, ensuring data availability, accuracy, and performance for business insights and machine learning models.


What We Are Looking For:

We are seeking an experienced and highly skilled Google Cloud Data Engineer who will be responsible for developing and managing data pipelines on GCP. The ideal candidate will bring strong expertise in cloud-based data processing, big data technologies, and data modeling to help us provide high-performance data solutions.


Responsibilities:

Data Pipeline Development and Management:

  • Design, build, and maintain scalable and reliable data pipelines using Cloud Dataflow, Cloud Pub/Sub, and Cloud Composer.
  • Develop ETL/ELT processes to process and transform large volumes of structured and unstructured data.
  • Optimize data pipeline performance, scalability, and reliability.
  • Ensure data processing and ingestion workflows are monitored and meet performance SLAs.

Data Storage and Management:

  • Design and implement data storage solutions using BigQuery, Cloud Storage, and Firestore.
  • Optimize data structures and partitioning for performance and cost efficiency.
  • Ensure data security, integrity, and availability in all storage solutions.
  • Manage data lifecycle policies and archiving processes.

Data Transformation and Processing:

  • Develop data transformation processes using BigQuery, Apache Beam, and Cloud Functions.
  • Implement data quality checks, validation rules, and monitoring solutions.
  • Support real-time and batch data processing needs.

Data Integration and Automation:

  • Integrate data from multiple sources, including APIs, databases, and third-party applications.
  • Automate data ingestion, transformation, and export using tools like Cloud Composer and Cloud Functions.
  • Ensure data consistency across different environments and systems.

Collaboration and Stakeholder Engagement:

  • Work closely with data scientists and analysts to understand data needs and business goals.
  • Provide technical guidance and best practices to the data engineering and business teams.
  • Collaborate with security and compliance teams to ensure data governance standards are met.

Performance Monitoring and Troubleshooting:

  • Monitor data pipeline performance and troubleshoot issues in real-time.
  • Analyze data pipeline failures and implement fixes to prevent recurrence.
  • Set up logging and monitoring using Stackdriver and Cloud Monitoring.


Qualifications:

  • Bachelor's degree in Computer Science, Data Engineering, or a related field; Master's degree is a plus.
  • 3+ years of experience in data engineering, with at least 2+ years working with Google Cloud Platform.
  • Google Professional Data Engineer certification is required.
  • Strong proficiency with GCP services such as BigQuery, Cloud Dataflow, Cloud Composer, Cloud Pub/Sub, Firestore, and Cloud Functions.
  • Hands-on experience with big data tools and frameworks such as Apache Beam, Hadoop, Spark, or Flink.
  • Hands-on experience with dbt.
  • Proficiency in programming languages such as Python, Java, or Scala.
  • Strong knowledge of SQL, data modeling, and query optimization.
  • Experience with CI/CD tools and version control (e.g., Git, Cloud Build).
  • Strong understanding of data governance, security, and compliance requirements.
  • Ability to manage large-scale data processing and real-time data pipelines.
  • Excellent problem-solving, analytical, and communication skills.
  • Must be a U.S. Citizen or Green Card holder.


Preferred Skills:

  • Experience with machine learning pipelines and AI/ML model deployment.
  • Familiarity with Terraform and Infrastructure as Code (IaC) principles.
  • Experience with NoSQL databases and key-value stores on GCP.
  • Knowledge of containerization and orchestration using Google Kubernetes Engine (GKE).


What We Offer:

  • Competitive salary and performance-based incentives.
  • Comprehensive health, dental, and vision coverage.
  • Professional development and training opportunities (including GCP certification).
  • Flexible work environment and remote work options.


Join us and be part of a team building innovative and scalable data solutions on Google Cloud Platform!


This position is open to multiple engagement models, including Permanent/Full-Time, Contract, or Corp-to-Corp (C2C) arrangements. We are looking for the best talent and are flexible on the employment structure for the right candidate.


This position is open to direct candidates only. We are not working with third-party agencies.


Candidates must be U.S. Citizens or Green Card holders.