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Entry Level Ibm Data Engineer Jobs in Texas (NOW HIRING)

Techvilla Solutions

Junior Data Engineer

Plano, TX

$109K - $131K/yr

Hands-on experience with IBM DataStage, SQL, Python, Snowflake, and dbt. * Basic understanding of ... Familiarity with cloud-based data platforms and modern data engineering practices. * Exposure to ...

New

CEDENT

DB2 SQL Data Engineer

Houston, TX · On-site

3 days onsite, Houston TX Senior DB2 SQL Data Engineer We are seeking a Senior DB2 SQL Data ... This role requires extensive hands-on experience in IBM iSeries tools like Aldon, RDI, and ACS ...

Varsity Brands

Data Engineer I

Farmers Branch, TX · On-site

$110K - $132K/yr

The Data Engineer I (DE I) is an entry-level engineering position responsible for contributing to the development of the enterprise data platform. This role applies foundational data engineering ...

Varsitybrands

Data Engineer I

Farmers Branch, TX · On-site

$110K - $132K/yr

The Data Engineer I (DE I) is an entry-level engineering position responsible for contributing to the development of the enterprise data platform. This role applies foundational data engineering ...

Pwc

Data Engineer - Senior Associate

San Antonio, TX · On-site

$77K - $202K/yr

... a Data Engineer - Senior Associate, you will focus on designing and building data infrastructure ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

ACCLiiVE

Azure Data Engr

Houston, TX · On-site

$52.50 - $65.25/hr

Azure Data Engr Location : Houston Duration : Long term contract Job Overview : Design and Build ... SSIS, IBM DataStage, etc.) Soft Skills: Ability to navigate and comprehend mapping documents ...

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Entry Level Ibm Data Engineer information

What are the key skills and qualifications needed to thrive as an entry level IBM data engineer?

To thrive as an Entry Level IBM Data Engineer, you need foundational knowledge in data modeling, SQL, programming (such as Python or Java), and a relevant degree in computer science or a related field. Familiarity with IBM data tools like Db2, IBM Cloud Pak for Data, and ETL platforms, as well as certifications such as IBM Certified Data Engineer, are highly beneficial. Strong analytical thinking, problem-solving abilities, and effective communication help you collaborate with teams and interpret business requirements. These skills ensure you can design, build, and maintain reliable data solutions that support organizational decision-making and innovation.

What is the difference between Entry Level Ibm Data Engineer vs Data Analyst?

AspectEntry Level Ibm Data EngineerData Analyst
Required CredentialsBachelor's in Computer Science, Data Science, or related field; IBM certifications beneficialBachelor's in Statistics, Mathematics, or related field; often requires proficiency in SQL and Excel
Work EnvironmentTech companies, data-driven organizations, often with cloud and IBM toolsBusiness environments, marketing, finance, with focus on data interpretation
Employer & Industry UsageUsed in IT, technology, and enterprise sectors utilizing IBM data toolsCommon across various industries for reporting and insights

While both roles involve working with data, Entry Level Ibm Data Engineers focus on building and maintaining data pipelines using IBM technologies, whereas Data Analysts primarily interpret data to generate reports and insights. The engineering role requires technical skills in data architecture, while analysts focus on data visualization and business understanding.

What does an entry level IBM data engineer do?

An Entry Level IBM Data Engineer is responsible for assisting in the design, development, and maintenance of data systems using IBM technologies and tools. They work with large datasets to extract, transform, and load (ETL) data, ensure data quality, and support data analytics initiatives. Typically, they collaborate with data scientists, analysts, and other engineers to support business intelligence, reporting, and machine learning projects. This role is ideal for those starting their careers in data engineering and often requires knowledge of programming languages like Python or SQL, as well as IBM software such as Db2 or IBM Cloud Pak for Data.

What are some common challenges faced by entry level IBM data engineers when working on data integration projects?

Entry-level IBM Data Engineers often face challenges such as understanding complex legacy data systems, ensuring data quality during migration, and aligning data formats across different sources. Collaborating with cross-functional teams—including business analysts, database administrators, and senior engineers—can help address these issues, but it requires strong communication skills and a willingness to ask questions. Over time, familiarity with IBM tools like DataStage and Cloud Pak for Data, along with hands-on experience, helps new engineers overcome these initial hurdles and contribute more effectively to integration projects.
What are the most commonly searched types of Ibm Data Engineer jobs in Texas? The most popular types of Ibm Data Engineer jobs in Texas are:
What are popular job titles related to Entry Level Ibm Data Engineer jobs in Texas? For Entry Level Ibm Data Engineer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Entry Level Ibm Data Engineer jobs in Texas look for? The top searched job categories for Entry Level Ibm Data Engineer jobs in Texas are:
What cities in Texas are hiring for Entry Level Ibm Data Engineer jobs? Cities in Texas with the most Entry Level Ibm Data Engineer job openings:
Entry Level Ibm Data Engineer jobs near you
Infographic showing various Entry Level Ibm Data Engineer job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Junior Data Engineer

Techvilla Solutions

Plano, TX

$109K - $131K/yr

Full-time

Posted 2 days ago

New

Job description

Required Experience
  • 1–3 years of experience in Data Engineering, ETL/ELT development, or Data Warehousing.
  • Hands-on experience with IBM DataStage, SQL, Python, Snowflake, and dbt.
  • Basic understanding of data warehousing concepts, dimensional modeling, and ETL/ELT processes.
  • Experience developing and maintaining data pipelines and transformation workflows.
  • Familiarity with cloud-based data platforms and modern data engineering practices.
  • Exposure to reporting, analytics, and Business Intelligence tools is an advantage.
  • Strong analytical, problem-solving, and communication skills.
Key Responsibilities
  • Develop, maintain, and optimize ETL/ELT pipelines using DataStage, Python, Snowflake, and dbt.
  • Design and implement data transformation workflows to support reporting and analytics.
  • Collaborate with business stakeholders to understand data requirements and translate them into technical solutions.
  • Analyze business and technical requirements to support data integration and reporting needs.
  • Write, optimize, and troubleshoot SQL queries for data extraction, transformation, and validation.
  • Build and maintain scalable data pipelines that ensure data quality, consistency, and reliability.
  • Perform data profiling, validation, and reconciliation to ensure data integrity.
  • Support the development and maintenance of data models and data warehouse structures.
  • Assist in identifying and resolving data quality issues and production incidents.
  • Work closely with Data Analysts, BI Developers, and other engineering teams to deliver high-quality data solutions.
  • Support dashboard and reporting initiatives by providing clean, reliable datasets.
  • Create and maintain technical documentation, ETL mappings, and data flow diagrams.
  • Participate in code reviews, testing, deployment, and continuous improvement activities.
  • Contribute to process automation and performance optimization initiatives.
Must-Have Technical Skills
  • IBM DataStage
  • SQL (query writing and optimization)
  • Python
  • Snowflake
  • dbt (Data Build Tool)
  • ETL/ELT Development
  • Data Warehousing Concepts
  • Data Modeling
  • Git or Version Control (preferred)
  • Basic understanding of cloud data platforms

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