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Data Engineer/Python

  • Job type Posted on: May 29, 2026
  • Experience level RIT Solutions
  • Employment type Malvern, Pennsylvania
  • Employment type Onsite
  • Salary Full-time

Job Title :

Data Engineer/Python

Job Type :

Full-time

Job Location :

Malvern Pennsylvania United States

Remote :

No

Jobcon Logo Job Description :

Senior Data Engineer Location: Malvern, PA (Hybrid) Experience Level: Level 4 (8+ years) Role Summary We are seeking a highly motivated Senior Data Engineer to join the Cost Basis Accounting and Method team. This role is primarily focused on a critical, multi-year Batch Modernization effort, moving legacy mainframe batch processes to a modernized AWS cloud-based architecture. The ideal candidate will be an independent contributor and a rockstar developer who is passionate about building scalable data pipelines. Key Responsibilities Design, develop, and maintain high-volume data transformation logic primarily using AWS Glue jobs written in Python. Develop custom code and potentially AWS Lambda functions for handling complex logic within the batch processes. Utilize PySpark and SQL for data querying, filtering, and manipulation against various data stores, including modernized data sources and initial DB2 tables. Collaborate with internal mainframe experts to understand legacy system logic and implement requirements for the modernized batch processes. Engage with the build and deployment pipeline, demonstrating a strong understanding of DevOps concepts and proficiency with Git/GitHub. Handle data ingestion from multiple sources, including various vendors, flat files, CSVs, and APIs. Work closely with a dedicated Tech Lead, but be prepared to operate with a high degree of independence. Required Skills and Qualifications AWS database experience, e.g. Aurora, Redshift. Proven experience as a Data Engineer with a strong focus on data pipelines and ETL/ELT processes. Expertise in Python (estimated 80–90% of development work). Experience with AWS services, particularly Glue and Lambda. Proficiency in PySpark and SQL for data handling and querying. Familiarity with DevOps practices and the Git/GitHub development workflow. Some experience with Java batch processes (estimated 10–20% of development work) is a plus. Experience in dealing with varied data formats and sources (vendors, files, APIs). Prior experience with or understanding of mainframe concepts is a good-to-have but not a requirement.

Jobcon Logo Position Details

Posted:

May 29, 2026

Reference Number:

14660_D47D0C2A8E26EC053CBA9C56788C6048

Employment:

Full-time

Salary:

Not Available

City:

Malvern

Job Origin:

APPCAST_CPC

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Senior Data Engineer Location: Malvern, PA (Hybrid) Experience Level: Level 4 (8+ years) Role Summary We are seeking a highly motivated Senior Data Engineer to join the Cost Basis Accounting and Method team. This role is primarily focused on a critical, multi-year Batch Modernization effort, moving legacy mainframe batch processes to a modernized AWS cloud-based architecture. The ideal candidate will be an independent contributor and a rockstar developer who is passionate about building scalable data pipelines. Key Responsibilities Design, develop, and maintain high-volume data transformation logic primarily using AWS Glue jobs written in Python. Develop custom code and potentially AWS Lambda functions for handling complex logic within the batch processes. Utilize PySpark and SQL for data querying, filtering, and manipulation against various data stores, including modernized data sources and initial DB2 tables. Collaborate with internal mainframe experts to understand legacy system logic and implement requirements for the modernized batch processes. Engage with the build and deployment pipeline, demonstrating a strong understanding of DevOps concepts and proficiency with Git/GitHub. Handle data ingestion from multiple sources, including various vendors, flat files, CSVs, and APIs. Work closely with a dedicated Tech Lead, but be prepared to operate with a high degree of independence. Required Skills and Qualifications AWS database experience, e.g. Aurora, Redshift. Proven experience as a Data Engineer with a strong focus on data pipelines and ETL/ELT processes. Expertise in Python (estimated 80–90% of development work). Experience with AWS services, particularly Glue and Lambda. Proficiency in PySpark and SQL for data handling and querying. Familiarity with DevOps practices and the Git/GitHub development workflow. Some experience with Java batch processes (estimated 10–20% of development work) is a plus. Experience in dealing with varied data formats and sources (vendors, files, APIs). Prior experience with or understanding of mainframe concepts is a good-to-have but not a requirement.

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