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Big Data Engineer Jobs in Dallas, TX (NOW HIRING)

Big Data Engineer

Dallas, TX · On-site

$51.50 - $68/hr

Big Data Engineer Location: Dallas, TX (Hybrid) JD: Summary We are looking for an experienced Big Data Engineer with 7-10 years of hands-on experience to design, build, and maintain scalable data ...

Big Data Engineer[Hybrid]

Dallas, TX · On-site

$55.25 - $73/hr

Skills Needed: Big Data, Spark SQL, Scala code, GCP Local to FL/TX/GA Position: Big Data Engineer Location: Temple Terrace, FL / Irving, Dallas TX / Alpharetta, GA (Hybrid - 3 Days in a Week Onsite ...

Full Time Role: Big Data Engineer

Dallas, TX · On-site

$55.50 - $73.25/hr

We are looking for an experienced Big Data Engineer with 7-10 years of hands-on experience to design, build, and maintain scalable data pipelines and processing systems in an on-premises Big Data ...

We are seeking a Data Engineer to help support large-scale enterprise big data platforms. This team is responsible for building and evolving modern data solutions that enable analytics across the ...

Big Data Engineer - Sr

Plano, TX · On-site

$53.50 - $71/hr

Data Engineer Location: Plano TX (3 Days/ Hybrid) Duration: 7 Months + Interview: 1 Round Role Summary * Large-scale enterprise migration initiative involving migration of existing data pipelines to ...

Senior Big Data Engineer

Plano, TX · On-site

$53.25 - $70.50/hr

Looking for true software engineering skill set. Experience working with large data sets, ETL, or applications that do high-volume data collection. Spark or other large scale data processing AWS ...

Big Data

Plano, TX · On-site

$50.75 - $65.75/hr

Must have strong programming knowledge of Core Java or Scala - Objects & Classes, Data Types ... Must have experience working on Big Data Processing Frameworks and Tools - MapReduce, YARN, Hive ...

Data Engineer

Plano, TX · On-site

$110K - $132K/yr

We are looking for a " Data Engineer " to fill its Full time position. If you are interested ... In-depth understanding and practical experience with optimized big data storage file formats such ...

Sr. Pyspark Data Engineer

Irving, TX · On-site

$109K - $132K/yr

The ideal candidate will have expertise in big data processing, ETL pipeline development, and cloud-based data engineering solutions. You will work closely with data analysts, data scientists, and ...

GCP Data Engineer

Richardson, TX · On-site

$104K - $124K/yr

GCP Data Engineer Location: Richardson, TX Duration: Long term contract Interview: F2F (Face to ... The ideal candidate will have hands-on expertise with GCP services, ETL/ELT processes, and big data ...

Data Engineer

Irving, TX · On-site

$125K - $140K/yr

Data Engineer We are seeking a highly skilled and motivated Data Engineer to play a pivotal role in ... Qualifications: • Big Data Frameworks Expertise: Demonstrated high proficiency in Apache Spark ...

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

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Big Data Engineer information

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How much do big data engineer jobs pay per hour?

As of Aug 30, 2026, the average hourly pay for big data engineer in Dallas, TX is $62.57, according to ZipRecruiter salary data. Most workers in this role earn between $53.27 and $70.43 per hour, depending on experience, location, and employer.

What does a Big Data Engineer do?

A Big Data Engineer designs, builds, and manages systems that process and store large volumes of data. They develop data pipelines, integrate data from various sources, and ensure that the infrastructure is scalable, reliable, and efficient. Their work enables organizations to analyze and derive insights from massive datasets, supporting decision-making and business intelligence. Big Data Engineers often work with technologies like Hadoop, Spark, and cloud platforms.

What are the key skills and qualifications needed to thrive as a Big Data Engineer?

To thrive as a Big Data Engineer, you need strong programming skills (often in Python, Java, or Scala), experience with data modeling, and a solid understanding of distributed computing and database systems, typically supported by a degree in computer science or a related field. Familiarity with big data tools and platforms like Hadoop, Spark, Kafka, and relevant cloud services, as well as certifications such as Cloudera or AWS Big Data, is also important. Analytical thinking, problem-solving ability, and effective communication are key soft skills that help bridge technical solutions with business needs. These skills are crucial for designing scalable data pipelines, ensuring efficient data processing, and delivering actionable insights that drive organizational success.

What are some common challenges Big Data Engineers face when working with large-scale data pipelines?

Big Data Engineers often encounter challenges related to optimizing data pipelines for scalability and reliability, especially as data volume and velocity increase. Issues like managing data consistency, handling schema changes, and ensuring low-latency data processing are frequent hurdles. Collaborating closely with data scientists and DevOps teams is crucial, as projects often require integrating diverse data sources and maintaining high data quality standards. Staying up-to-date with evolving big data technologies and best practices is essential to address these ongoing challenges effectively.
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Infographic showing various Big Data Engineer job openings in Dallas, TX 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, with an average salary of $130,142 per year, or $62.6 per hour.

Big Data Engineer

Wise Skulls

Dallas, TX • On-site

$51.50 - $68/hr

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Title: Big Data Engineer
Location: Dallas, TX (Hybrid)
JD:
Summary
We are looking for an experienced Big Data Engineer with 7-10 years of hands-on experience to design, build, and maintain scalable data pipelines and processing systems in an on-premises Big Data environment. Beyond strong individual contribution, the ideal candidate will own architecture and design decisions, set technical direction, and mentor and support other developers on the team. The role works closely with cross-functional teams to deliver reliable, high-quality data solutions that support business and analytics needs.
Roles & Responsibilities
  • Lead the design, development, and maintenance of robust, scalable data pipelines for ingestion, transformation, and processing of large datasets in an on-premises environment.
  • Own architectural and design decisions for data solutions, evaluating trade-offs and defining technical standards for the team.
  • Mentor, guide, and support other data engineers through code reviews, design reviews, technical coaching, and hands-on problem-solving.
  • Build and optimize data workflows using Python, Spark, and the Hadoop ecosystem.
  • Work extensively with Hadoop ecosystem components (Hive, HDFS, Impala) to manage and query large-scale data.
  • Manage and optimize batch scheduling and job orchestration using enterprise schedulers such as CA7 or Control-M.
  • Ensure data quality, integrity, and performance across data platforms.
  • Collaborate with data analysts, data scientists, and business stakeholders to translate data requirements into sound technical designs.
  • Troubleshoot and resolve complex issues in data pipelines and production environments, acting as an escalation point for the team.
  • Champion best practices for coding standards, version control, testing, and documentation.
  • Stay current with emerging technologies, particularly AI/ML capabilities, and identify opportunities to apply them to data engineering workflows.

Technical Skills
Must Have
  • 7-10 years of overall experience in data engineering, with a proven track record in technical leadership (design ownership, mentoring, guiding development teams).
  • Python - strong hands-on development experience building production-grade data solutions.
  • Big Data / Hadoop ecosystem (Hadoop, Hive, Impala, HDFS) - deep, hands-on experience in on-premises environments.
  • Apache Spark - solid experience developing and tuning large-scale distributed data processing jobs.
  • Job scheduling / orchestration - hands-on experience with CA7 or Control-M (or comparable enterprise schedulers).
  • Strong understanding of data structures, ETL processes, and SQL.
  • Extensive experience with large-scale data processing and distributed systems.
  • Demonstrated ability to make sound architecture/design decisions and to mentor and support other developers.
  • Exposure to AI/ML concepts or tools, with a strong willingness to learn and grow in this space.
  • Banking/Financial domain highly preferred