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Hadoop Data Engineer Jobs in Texas (NOW HIRING)

Palnar

Hadoop Data Engineer

Austin, TX · On-site

5+ years of development and maintenance experience with Hadoop eco-system (Spark, Oozie, HDFS, Yarn, Hive) with experience on real-time & stream processing systems. Good knowledge of Java is needed ...

Incedo Inc

Hadoop Data Engineer

Dallas, TX · On-site

$113K - $136K/yr

Sr. Feature Engineer Dallas,TX/ Pittsburgh, PA / Clevland OH Tech: Data Engineering/Pipeline MLOps Engineering/Pipeline OpenShift Git Linux Programming language: Python SQL Spark Hive Title Skillsets ...

Northern Base

Hadoop Architect

Plano, TX · On-site

Hadoop Architect Experience: Minimum10 years Key Responsibilities · Monitor and resolve HDFS and ... Data Support Engineer position. If this is for an interview, I can also prepare: 1. The top 50 ...

Wise Skulls

Big Data Engineer

Dallas, TX · On-site

$51.50 - $68/hr

Title: Big Data Engineer Location: Dallas, TX (Hybrid) JD: Summary We are looking for an ... Work extensively with Hadoop ecosystem components (Hive, HDFS, Impala) to manage and query large ...

Systech Corp, Inc.

Data Engineer

Texas City, TX · On-site

$98K - $117K/yr

Data Engineer We are looking for an experienced Data Engineer with 8+ years of experience in ... Experience with Apache Spark, PySpark, and Hadoop. * Strong knowledge of data warehousing and data ...

Ruri Software Technologies LLC

GCP Data Engineer

Irving, TX · On-site

$109K - $132K/yr

Big data expert with 6+ years experience in Hadoop Big data ecosystem * Spark - Batch & Streaming (Python,Scala ) * Apache Kafka hands on experience * Experience in cloud environment, specially GCP

Saxon Global

Data Engineer

Frisco, TX

$107K - $128K/yr

... Hadoop, Hive, Spark, columnar databases, etc. Maintain metadata, data catalogue and data lineage information. Collaborate with data engineers and analytics and subject matter experts to identify ...

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How much do hadoop data engineer jobs pay per hour?

As of Aug 29, 2026, the average hourly pay for hadoop data engineer in Texas is $58.88, according to ZipRecruiter salary data. Most workers in this role earn between $51.49 and $68.75 per hour, depending on experience, location, and employer.

What is a Hadoop data engineer?

Hadoop Data Engineers are IT professionals who design, build, and maintain large-scale data processing systems using the Hadoop ecosystem. They are responsible for developing and managing complex data pipelines, ensuring the efficient storage, processing, and retrieval of big data. Their work involves using tools like HDFS, MapReduce, Hive, and Spark to process massive datasets, often in support of data analytics or machine learning initiatives. Hadoop Data Engineers also optimize data workflows, troubleshoot issues, and collaborate with data scientists and analysts to deliver reliable data solutions.

What are some typical challenges a Hadoop data engineer faces when managing large-scale data pipelines?

Hadoop Data Engineers often encounter challenges such as optimizing data processing jobs for performance, ensuring data integrity across distributed systems, and managing the scalability of clusters as data volumes grow. Troubleshooting job failures due to resource constraints or data inconsistencies is also common. Additionally, collaborating with data scientists and analysts to ensure data is transformed and made accessible in a timely manner is a key part of the role.

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

To thrive as a Hadoop Data Engineer, you need strong programming skills (especially in Java, Python, or Scala), a solid understanding of distributed computing concepts, and a background in computer science or related fields. Familiarity with Hadoop ecosystem tools like HDFS, Hive, Pig, Spark, and workflow schedulers such as Oozie, as well as knowledge of big data certifications (e.g., Cloudera Certified Associate), are typically required. Analytical thinking, problem-solving, and effective communication are crucial soft skills for collaborating with cross-functional teams and translating business requirements into technical solutions. These skills and qualifications are essential for efficiently processing large datasets, ensuring data integrity, and delivering scalable data solutions that support organizational goals.

What is the difference between Hadoop Data Engineer vs Data Analyst?

AspectHadoop Data EngineerData Analyst
Required SkillsBig data tools, Hadoop ecosystem, SQL, Java/ScalaData visualization, SQL, Excel, statistical analysis
Work EnvironmentData engineering teams, cloud platforms, big data infrastructureBusiness units, reporting tools, data visualization platforms
CertificationsHadoop certifications, cloud certificationsNone specific, often data analysis or visualization certifications

The main difference between a Hadoop Data Engineer and a Data Analyst lies in their focus: Hadoop Data Engineers build and maintain big data infrastructure using Hadoop and related tools, while Data Analysts interpret data to generate insights using analysis and visualization tools. Both roles require strong SQL skills, but the engineering role emphasizes big data technologies and infrastructure development.

What are popular job titles related to Hadoop Data Engineer jobs in Texas?

For Hadoop Data Engineer jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Hadoop Data Engineer jobs in Texas look for?

The top searched job categories for Hadoop Data Engineer jobs in Texas are:

Hadoop Data Engineer jobs near you
Infographic showing various Hadoop Data Engineer job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $122,474 per year, or $58.9 per hour.

Hadoop Data Engineer

Palnar

Austin, TX • On-site

Full-time

Re-posted 28 days ago

Job description

5+ years of development and maintenance experience with Hadoop eco-system (Spark, Oozie, HDFS, Yarn, Hive) with experience on real-time & stream processing systems. Good knowledge of Java is needed along with Production support experience. Should have knowledge in different Hadoop Distribution systems like CDH, CDP, MapR etc. Good to have experience with Python scripting and AWS, Airflow

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