Python/PySpark Data Engineer

Charlotte, NC, US • Posted 2 days ago • Updated 2 days ago
Contract Corp To Corp
Contract W2
12 Months
No Travel Required
On-site
Depends on Experience
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Python
  • PySpark
  • Apache Kafka
  • Data Governance
  • Data Management
  • Data Quality
  • Data Warehouse

Summary

We are looking for a strong Python/PySpark Data Engineer to build scalable data ingestion and integration pipelines across enterprise data sources and metadata platforms. The engineer will work with metadata catalogs, databases, APIs, and batch/Realtime integration patterns while contributing to enterprise data management and data warehousing initiatives.

 

Key Responsibilities

•           Develop robust data engineering solutions using Python, PySpark and Apache Spark.

•           Consume and integrate metadata/data from Ab Initio Enterprise Meta>Environment (EME/EMH), Oracle databases, and ServiceNow APIs.

•           Perform source-to-target mapping, data transformation, validation, and reconciliation.

•           Build and maintain batch data ingestion and integration pipelines.

•           Work with data warehouse concepts, data models, metadata management, data lineage and data quality.

•           Integrate technical and business metadata from multiple enterprise sources.

•           Understand existing/custom data engineering frameworks and quickly develop solutions within them.

•           Troubleshoot performance, data quality, and integration issues across large datasets.

Required Skills

•           Strong hands-on expertise in Python-based data engineering.

•           Strong experience with PySpark / Apache Spark and large-scale data processing.

•           Experience working with Oracle/SQL and relational databases.

•           Experience consuming REST APIs and integrating API-based data sources.

•           Good understanding of ETL/ELT, source-to-target mapping, data warehousing and dimensional/relational data modeling.

•           Understanding of metadata management, business/technical metadata, lineage and data governance concepts.

•           Experience building production-grade batch ingestion/integration pipelines.

•           Ability to understand and work with custom enterprise data frameworks.

Good to Have

•           Experience with real-time/streaming integration, such as Kafka or Spark Structured Streaming.

•           Exposure to Google Cloud Platform (Google Cloud Platform) and its data services.

•           Experience with enterprise metadata/catalog solutions, particularly Ab Initio metadata environments.

•           Experience integrating with ServiceNow.

Ideal Profile: A hands-on engineer who is particularly strong in Python + PySpark, understands enterprise data and metadata ecosystems, and can quickly learn existing frameworks rather than relying only on off-the-shelf ETL tools.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10124157
  • Position Id: 9125774
  • Posted 2 days ago
Contact the job poster
IA

Imran Ali

Recruiter @ e-IT Professionals Corp.

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