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Data Transformation Jobs in Texas (NOW HIRING)

Photon

SPARK Data Onboarding Engineer- NJ

Addison, TX · On-site

Implement efficient data transformation and aggregation using PySpark and relevant big data frameworks. * Develop robust error handling and exception management mechanisms to ensure data integrity ...

Oscar Technology

Data Engineer

Grand Prairie, TX · On-site

$109K - $131K/yr

Develop data ingestion, transformation, and integration workflows using SQL and Python. * Design and implement Lakehouse and Medallion architecture solutions. * Work with cloud data platforms ...

New

S3b Global Inc

Data Modeler with SAP Hana

Dallas, TX · On-site

$54.25 - $70.25/hr

Understand data and prepare data transformation logics and data quality logics * Create and document data mapping, including data dictionaries, metadata, and entity-relationship diagrams.

Ascentt

Data Engineer

Plano, TX · On-site

$110K - $132K/yr

... transformation, automation, and analytics • Collaborate with cross-functional teams including Data Analysts, Data Scientists, Product teams, and Business stakeholders to deliver data-driven ...

Tata Consultancy Service Limited

Data Engineer

Dallas, TX · On-site

$105K - $120K/yr

... data transformation frameworks. • Develop and optimize Snowflake databases, schemas, and data pipelines. • Leverage Snowflake CoCo capabilities to accelerate data engineering activities. • ...

Ascentt

Data Engineer

Plano, TX · On-site

$110K - $132K/yr

... transformation, automation, and analytics • Collaborate with cross-functional teams including Data Analysts, Data Scientists, Product teams, and Business stakeholders to deliver data-driven ...

Rysun Labs Inc

Data Technical Architect

Houston, TX · On-site

$70/hr

Rysun guides and accelerates the AI & Data strategy and Digital Transformation programs for Fortune 2000 enterprises and product startups to shape remarkable customer experiences and intelligent ...

Ascentt

Data Engineer

Plano, TX · On-site

$109K - $131K/yr

Write clean, efficient, and production-ready SQL queries and Python code for data transformation, automation, and analytics * Collaborate with cross-functional teams including Data Analysts, Data ...

Tata Consultancy Service Limited

Data Engineer

Dallas, TX · On-site

$105K - $120K/yr

... transformation frameworks. • Develop and optimize Snowflake databases, schemas, and data pipelines. • Implement data quality controls, reconciliation processes, and monitoring frameworks. • ...

Saransh Inc

Snowflake Data Engineer - Onsite

Westlake, TX · On-site

$109K - $132K/yr

Develop and implement data transformation and loading process to populate and maintain data within the created tables and views. * Collaborate with data architects and tech leads to understand data ...

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Data Transformation information

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

To thrive in a Data Transformation role, a strong background in data analysis, data modeling, and database management is essential, often supported by a degree in computer science, information systems, or a related field. Proficiency with data transformation tools like SQL, ETL platforms (such as Informatica or Talend), and cloud data services is typically required, and certifications in these areas can be advantageous. Strong problem-solving skills, attention to detail, and effective communication abilities are key for collaborating with cross-functional teams and addressing complex data challenges. These skills and qualities are important because they ensure accurate, efficient data transformations that support critical business decisions.

What are the typical daily responsibilities of someone in a data transformation role?

In a Data Transformation role, your daily responsibilities often include analyzing raw data from multiple sources, designing and executing processes to clean and reformat data, and collaborating with business and IT teams to ensure data meets project requirements. You’ll typically work with ETL (Extract, Transform, Load) tools to automate and streamline these processes, as well as perform quality checks to validate data accuracy. Coordinating with data engineers, data analysts, and stakeholders is a key part of the job to ensure projects align with business goals. Staying up-to-date with new data management technologies and best practices can also be a regular part of your routine, helping to drive ongoing improvements.

What is a data transformation?

A Data Transformation job involves converting, structuring, and optimizing raw data to make it useful for analysis, reporting, or other business processes. Professionals in this role use ETL (Extract, Transform, Load) tools, coding languages like SQL or Python, and cloud platforms to clean, aggregate, and reformat data. They ensure data integrity, improve accessibility, and support data-driven decision-making. This role is essential in industries that rely on accurate and efficient data processing, such as finance, healthcare, and e-commerce.

What are popular job titles related to Data Transformation jobs in Texas? For Data Transformation jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Data Transformation jobs in Texas look for? The top searched job categories for Data Transformation jobs in Texas are:
Data Transformation jobs near you
Infographic showing various Data Transformation job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 10% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

SPARK Data Onboarding Engineer- NJ

Photon

Addison, TX

Full-time

Re-posted 3 days ago

Job description

Job Title: PySpark Data Engineer

Summary:

We are seeking a skilled PySpark Data Engineer to join our team and drive the development of robust data processing and transformation solutions within our data platform. You will be responsible for designing, implementing, and maintaining PySpark-based applications to handle complex data processing tasks, ensure data quality, and integrate with diverse data sources. The ideal candidate possesses strong PySpark development skills, experience with big data technologies, and the ability to work in a fast-paced, data-driven environment.

Key Responsibilities: Data Engineering Development:
  • Design, develop, and test PySpark-based applications to process, transform, and analyze large-scale datasets from various sources, including relational databases, NoSQL databases, batch files, and real-time data streams.
  • Implement efficient data transformation and aggregation using PySpark and relevant big data frameworks.
  • Develop robust error handling and exception management mechanisms to ensure data integrity and system resilience within Spark jobs.
  • Optimize PySpark jobs for performance, including partitioning, caching, and tuning of Spark configurations.
Data Analysis and Transformation:
  • Collaborate with data analysts, data scientists, and data architects to understand data processing requirements and deliver high-quality data solutions.
  • Analyze and interpret data structures, formats, and relationships to implement effective data transformations using PySpark.
  • Work with distributed datasets in Spark, ensuring optimal performance for large-scale data processing and analytics.
Data Integration and ETL:
  • Design and implement ETL (Extract, Transform, Load) processes to ingest and integrate data from various sources, ensuring consistency, accuracy, and performance.
  • Integrate PySpark applications with data sources such as SQL databases, NoSQL databases, data lakes, and streaming platforms
Qualifications and Skills:
  • Bachelor's degree in Computer Science, Information Technology, or a related field.
  • 5+ years of hands-on experience in big data development, preferably with exposure to data-intensive applications.
  • Strong understanding of data processing principles, techniques, and best practices in a big data environment.
  • Proficiency in PySpark, Apache Spark, and related big data technologies for data processing, analysis, and integration.
  • Experience with ETL development and data pipeline orchestration tools (e.g., Apache Airflow, Luigi).
  • Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
  • Excellent communication and collaboration skills to work effectively with data analysts, data architects, and other team members.

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