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Full Time Data Transformation Jobs (NOW HIRING)

Loopback LLC

Data Engineer

Dallas, TX

$113.30K - $136K/yr

All applicants must be currently authorized to work in the United States on a full-time basis. Role ... Own and maintain data transformation logic, codebases, and supporting documentation * Model and ...

VTG

Data Engineer

Chantilly, VA

$118.30K - $142.10K/yr

... transformation pipelines in Palantir's environment. The Data Engineer will also integrate with ... UNAVAILABLEEmployment Type: FULL_TIME

Onebridge

Data Engineer

Lawrence Township, NJ · On-site

$127.30K - $152.90K/yr

Execute complex SQL queries to validate sourcetotarget mappings, transformation logic, and data ... Employment Type: FULL_TIME

Loopback LLC

Data Engineer

Dallas, TX · On-site

$113.30K - $136K/yr

All applicants must be currently authorized to work in the United States on a full-time basis. Role ... Own and maintain data transformation logic, codebases, and supporting documentation * Model and ...

BlackLine

Staff Data Engineer

Manhattan, NY · On-site

$193K - $242K/yr

Design and build infrastructure for optimal extraction, transformation, and loading (ETL) of data ... Employee Referral Bonus Amount$1,500Employment Type: FULL_TIME

CitiusTech

Senior Data Architect

Manhattan, NY · On-site

$150K - $180K/yr

Lead end-to-end data transformation initiatives, migrating legacy platforms to Snowflake and/or ... type Full-time Job function Information Technology Industries IT Services and IT Consulting ...

AceStack LLC

Remote Type: Full-time / Contract Overview We are seeking an experienced SAP Data Engineer with ... Proficiency with ETL tools, data modeling, and data transformation frameworks (e.g., BODS, SAP Data ...

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Full Time Data Transformation information

What are the key skills and qualifications needed to thrive as a Full Time Data Transformation Specialist, and why are they important?

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 a Full Time Data Transformation job?

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 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:
What job categories do people searching Full Time Data Transformation jobs look for? The top searched job categories for Full Time Data Transformation jobs are:
Full Time Data Transformation jobs near you
Infographic showing various Full Time Data Transformation job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution.

Data Engineer

Loopback LLC

Dallas, TX

$113.30K - $136K/yr

Full-time

Posted yesterday

Job description

This employer will not sponsor applicants for employment visa status (e.g., H1-B) for this position. All applicants must be currently authorized to work in the United States on a full-time basis.

Role Summary

Loopback Health is seeking an innovative and team-oriented Data Engineerto join our team. In this role, you will be responsible for designing, building, and maintaining scalable data pipelines and transformation processes that power analytics and client solutions. You will play a critical role in managing data flows, ensuring data quality, and collaborating with cross-functional teams to drive system and process improvements. Additionally, you will support the design, implementation, and maintenance of key clinical and enterprise datasets.


Key Responsibilities

  • Design, build, and maintain scalable data pipelines to ingest, transform, and deliver data across diverse sources and environments
  • Develop and manage ETL/ELT processes within cloud-based data platforms (e.g., Snowflake, Databricks)
  • Own and maintain data transformation logic, codebases, and supporting documentation
  • Model and optimize data structures within data lakes and data warehouses to support analytics and reporting use cases
  • Ensure data reliability, integrity, and performance to meet client and application SLA requirements
  • Manage evolving data ingestion formats across Health Systems, Life Sciences, and Enterprise partner ecosystems
  • Drive automation and continuous improvement of data workflows to reduce manual effort and increase efficiency
  • Implement data quality checks, monitoring, and validation processes
  • Collaborate with business and technical stakeholders to gather requirements and translate them into scalable data solutions
  • Develop and promote best practices in data engineering, data modeling, and pipeline design
  • Conduct data profiling and support testing efforts in partnership with QA and DevOps teams


Qualifications

Required:

  • 3-5 years of experience in Data Engineering, Data Integration, or a related field
  • Experience designing and building data pipelines and transformation workflows
  • Hands-on experience with cloud data platforms (Snowflake, Databricks) and cloud environments (Azure)
  • Strong experience with SQL and at least one programming language (e.g., Python, C#)
  • Experience with relational and non-relational data modeling, schema design, and performance optimization
  • Familiarity with data lake and data warehouse architecture

Preferred:

  • Experience working with healthcare or clinical data
  • Knowledge of data orchestration tools and workflow management
  • Experience implementing data quality frameworks and automated testing
  • Ability to communicate complex technical concepts to both technical and non-technical stakeholders

Soft Skills

  • Detail-oriented and data-driven.
  • Proactive in identifying inefficiencies and suggesting pragmatic solutions.
  • Comfortable working in a cross-functional, data-intensive environment.
  • Strong communication and documentation skills.


All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, or national origin.

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