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Data Engineer Jobs in Reading, PA (NOW HIRING)

Penske

Data Scientist

Reading, PA · On-site

Practical experience programming using Python, R or other high level scripting languages is ... Experience with ELT Processes, data visualization and reporting tools, including Power BI or ...

Penske

Data Scientist

Reading, PA · On-site

Practical experience programming using Python, R or other high level scripting languages is ... Experience with ELT Processes, data visualization and reporting tools, including Power BI or ...

Element Materials Technology

Data Processor

Reading, PA · On-site

Element has an opportunity for a Data Processor to join our rapidly expanding team. As a member of ... Propose engineering documents for clients' approval, on-site installation and hands-on monitoring ...

Mondo

Senior Maintenance Analyst

Reading, PA · On-site

$55 - $70/hr

Collaborate with data science, engineering, and reporting teams to deliver standardized data products * Evaluate and recommend appropriate technologies based on business requirements, cost, and ...

Penske

Data Analyst

Reading, PA

Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or related field Experience working with large datasets and applying analytical techniques Strong programming skills in ...

Penske

Data Analyst

Reading, PA · On-site

Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or related field Experience working with large datasets and applying analytical techniques Strong programming skills in ...

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Showing results 21-40

All JobsData Engineer JobsData Engineer Jobs in Reading, PA

Data Engineer information

See Reading, PA salary details

$42.7K

$124.6K

$170.5K

How much do data engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for data engineer in Reading, PA is $124,573.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,000.00 and $132,000.00 per year, depending on experience, location, and employer.

What is a data engineer?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

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

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What does a data engineer do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

How do data engineers typically collaborate with data scientists and analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior-level role that requires experience with programming, databases, and data pipeline tools. Entry-level positions may be available for those with relevant internships or strong foundational skills, but most data engineering roles demand several years of experience or advanced knowledge of tools like SQL, Python, and cloud platforms.

What is the role of a data engineer?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, process, and store large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible and reliable for analysis and decision-making.
More about Data Engineer jobs

What are the most commonly searched types of Data Engineer jobs in Reading, PA?

The most popular types of Data Engineer jobs in Reading, PA are:

What are popular job titles related to Data Engineer jobs in Reading, PA?

For Data Engineer jobs in Reading, PA, the most frequently searched job titles are:

What job categories do people searching Data Engineer jobs in Reading, PA look for?

The top searched job categories for Data Engineer jobs in Reading, PA are:

What cities near Reading, PA are hiring for Data Engineer jobs?

Cities near Reading, PA with the most Data Engineer job openings:

Data Engineer jobs near you
Infographic showing various Data Engineer job openings in Reading, PA as of August 2026, with employment types broken down into 85% Full Time, 7% Temporary, and 8% Contract. Highlights an 71% In-person, 9% Hybrid, and 20% Remote job distribution, with an average salary of $124,573 per year, or $59.9 per hour.

Senior Data Operations Analyst

Goodville Mutual Casualty Company

New Holland, PA • On-site

$80K - $101K/yr

Full-time

Re-posted 7 days ago

Job description

Description

This position will be responsible for unifying data sources to deliver actionable insights that enhance underwriting, pricing, claims management, and customer experience. This position is central to boosting profitability, reducing fraud, and supporting strategic modernization initiatives. This position will ensure that enterprise reporting is accurate, consistent, and reliable by validating data quality, enforcing business rules, and collaborating with engineering, QA, and business teams. 


Functions:

  • Manage and validate centralized data repositories, ensuring accuracy and timely updates.
  • Validate and reconcile data from source systems to data warehouses and semantic models.
  • Investigate and document data issues, collaborating with engineering and QA teams.
  • Ensure compliance with regulatory requirements in all data handling activities.
  • Develop and maintain operational dashboards and reports using Power BI.
  • Assist in migrating legacy reports to BI platforms and contribute to report design and validation.
  • Manage semantic models, datasets, and report distributions.
  • Support operational reporting with a focus on data trust and accuracy.
  • Engage stakeholders to clarify reporting requirements and enforce business rules.
  • Collaborate across departments to drive data governance.
  • Administer workflows including nightly, month end, quarter end and year end processing and troubleshoot report issues.
  • Monitor data for process improvements and operational efficiency.
  • Perform other duties as needed.


Requirements

  • Bachelor's degree in data science, Statistics, Actuarial Science, or a related field preferred.
  • 8+ years of experience in data analysis or business intelligence within insurance industry required.
  • Proficiency in SQL, Excel, and Python required.
  • Experience with Power BI, ETL, and data warehousing required.
  • Familiarity with Medallion Architecture and Microsoft Fabric required.
  • Knowledge of property & casualty insurance, rating structures, actuarial concepts, and risk modeling required.
  • Understanding insurance operations, KPIs, and regulatory requirements required.
  • Prior experience working with Origami and / or Assure Claims DXC products preferred
  • Ability to collaborate with Data Engineers, QA, Power BI teams, Scrum Masters, and Business Stakeholders preferred.
  • Ability to work flexible hours, travel to all organization offices (including in Pennsylvania, Ohio, and South Dakota) and travel to vendor work sites required.
  • Ability to work in an office environment with moderate noise level, remain in a stationary position and operate a computer a majority of the time required.
  • Ability to move throughout the office to access work materials and to move work materials weighing up to ten pounds daily required.
  • Ability to perform the essential functions of the job with or without reasonable accommodation required.


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