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Data Engineering Specialist Jobs (NOW HIRING)

LTM

Specialist - Data Engineering

Tampa, FL · On-site

$108K - $129K/yr

LTM is seeking a Senior Big Data Engineer to design and implement scalable data processing solutions. The role involves developing and maintaining robust data pipelines, collaborating with data ...

HBK Engineering, LLC

Engineering Specialist

Spring, TX · On-site

About this Role An Engineering Specialist at HBK Engineering is a position that combines advanced ... Analyze information from supplementary data sources including topographical survey, utility atlas ...

Group O

Reliability Engineering Specialist

Fort Worth, TX · On-site

$50K - $80K/yr

Reliability Engineering Specialist Department: Engineering Employment Type: Full Time Location ... Analyzes reliability and production data to identify trends, determine root causes, and drive ...

DXC Technology

Data Engineering Lead

Charleston, SC · On-site

Lead and mentor a team of Data Engineers, Data Architects, and Data Integration specialists. * Establish engineering best practices and technical standards. * Provide technical oversight ...

Owens Corning

Engineering Specialist

Charlotte, NC · On-site

Purpose of the Job The ERP Implementation Engineer / Specialist serves as a subject matter expert ... Product Configuration & Master Data * Partner with business subject matter experts to develop and ...

Owens Corning

Engineering Specialist

Charlotte, NC · On-site

Purpose of the Job The ERP Implementation Engineer / Specialist serves as a subject matter expert ... Product Configuration & Master Data * Partner with business subject matter experts to develop and ...

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All JobsData Engineering Specialist Jobs

Data Engineering Specialist information

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$33K

$81.5K

$140K

How much do data engineering specialist jobs pay per year?

As of Jul 24, 2026, the average yearly pay for data engineering specialist in the United States is $81,518.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,500.00 and $96,500.00 per year, depending on experience, location, and employer.

What are Data Engineering Specialists?

Data Engineering Specialists are professionals who design, build, and maintain the infrastructure that allows organizations to collect, store, and analyze large amounts of data. They develop data pipelines, manage databases, and ensure data is accessible, reliable, and secure for analytics and business intelligence purposes. Their work is crucial in transforming raw data into usable formats for data scientists, analysts, and business leaders.

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

To thrive as a Data Engineering Specialist, you need expertise in database management, data modeling, ETL processes, and programming languages such as SQL, Python, or Scala, often supported by a degree in computer science or a related field. Proficiency with big data platforms (e.g., Hadoop, Spark), cloud services (AWS, Azure, GCP), and data pipeline orchestration tools is typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you collaborate with cross-functional teams and address complex data challenges. These skills are essential for building robust, scalable data infrastructure that empowers organizations to make data-driven decisions.

How do Data Engineering Specialists typically collaborate with data scientists and analysts within an organization?

Data Engineering Specialists work closely with data scientists and analysts by designing, building, and maintaining data pipelines that ensure reliable, high-quality data is readily available. They often meet regularly with these teams to understand data requirements, troubleshoot data issues, and optimize workflows for analytics and machine learning projects. Effective collaboration involves clear communication about data structures, definitions, and timelines, as well as actively participating in code reviews and joint problem-solving sessions. This teamwork is essential for delivering impactful, data-driven solutions across the organization.

What is the difference between Data Engineering Specialist vs Data Engineer?

AspectData Engineering SpecialistData Engineer
CredentialsBachelor's in CS, certifications like AWS, GCP, or AzureBachelor's in CS, related certifications
Work EnvironmentData teams, cloud platforms, data warehousesData pipelines, databases, cloud environments
Industry UsageUsed across tech, finance, healthcareCommon in similar industries, focus on data infrastructure
Search IntentUnderstanding roles, skills, and career pathJob requirements, skills, and responsibilities

Data Engineering Specialists focus on designing and maintaining data pipelines, often with specialized skills in cloud platforms. Data Engineers build and optimize data infrastructure, working on data collection, storage, and processing. Both roles overlap in skills and environment but differ in scope and focus.

More about Data Engineering Specialist jobs
What job categories do people searching Data Engineering Specialist jobs look for? The top searched job categories for Data Engineering Specialist jobs are:
Data Engineering Specialist jobs near you
Infographic showing various Data Engineering Specialist job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $81,518 per year, or $39.2 per hour.

Specialist - Data Engineering

LTM

Tampa, FL • On-site

$108K - $129K/yr

Full-time

Posted 8 days ago

Job description

Job Summary:
LTM is seeking a Senior Big Data Engineer to design and implement scalable data processing solutions. The role involves developing and maintaining robust data pipelines, collaborating with data scientists, and ensuring data quality across large datasets.
Responsibilities:
• Design develop and optimize scalable data processing applications leveraging Apache Spark
• Write clean efficient and reusable Python code to support data engineering tasks
• Analyze complex data sets to identify trends and insights for business use
• Collaborate with stakeholders to gather requirements and deliver data solutions that meet business needs
• Mentor junior team members and contribute to sharing knowledge within the team
• Participate in code reviews and ensure adherence to coding standards and best practices
• Manage data pipeline deployments and monitor their health in production environments
Qualifications:
Required:
• 5 to 7 years of experience skilled in Apache Spark and Python
• Design and implement scalable data processing solutions
• Develop and maintain robust data pipelines using Apache Spark and Python
• Collaborate with data scientists and analysts to optimize data workflows
• Ensure data quality and integrity across large datasets
• Implement data transformations and aggregations for analytics and reporting
• Work with cross-functional teams to integrate data solutions into existing systems
• Monitor and troubleshoot data processing jobs to ensure reliability and performance
• Stay updated with emerging technologies and best practices in big data and Python development
• Design develop and optimize scalable data processing applications leveraging Apache Spark
• Write clean efficient and reusable Python code to support data engineering tasks
• Analyze complex data sets to identify trends and insights for business use
• Collaborate with stakeholders to gather requirements and deliver data solutions that meet business needs
• Mentor junior team members and contribute to sharing knowledge within the team
• Participate in code reviews and ensure adherence to coding standards and best practices
• Manage data pipeline deployments and monitor their health in production environments
Company:
LTM is a worldwide technology consulting and digital solutions company that empowers businesses in a variety of sectors. Founded in 1996, the company is headquartered in Mumbai, IND, with a team of 10001+ employees. The company is currently Late Stage.

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