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Senior Data Engineer - Oracle, Spark & Cloud Analytics

Charlotte, NC, US • Posted 10 hours ago • Updated 34 minutes ago

Full Time

On-site

Fitment

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Job Details

Skills

Migration
Reporting
Real-time
Replication
Collaboration
Data Processing
Data Engineering
PySpark
Scala
Python
Database
OLAP
Extract
Transform
Load
ELT
Batch Processing
SQL
Data Modeling
Oracle GoldenGate
Change Data Capture
Data Integration
Oracle Exadata
Cloud Storage
Data Flow
Apache Kafka
Apache Hadoop
Microsoft Azure
OCI
Data Migration
Oracle
Analytical Skill
Data Warehouse
Apache Spark
Performance Tuning
Cloud Computing
Analytics
Google Cloud Platform
Google Cloud

Migration
Reporting
Real-time
Replication
Collaboration
Data Processing
Data Engineering
PySpark
Scala
Python
Database
OLAP
Extract
Transform
Load
ELT
Batch Processing
SQL
Data Modeling
Oracle GoldenGate
Change Data Capture
Data Integration
Oracle Exadata
Cloud Storage
Data Flow
Apache Kafka
Apache Hadoop
Microsoft Azure
OCI
Data Migration
Oracle
Analytical Skill
Data Warehouse
Apache Spark
Performance Tuning
Cloud Computing
Analytics
Google Cloud Platform
Google Cloud

Summary

Summary:
We are seeking an experienced Senior Data Engineer with deep expertise in Oracle-based analytical platforms and Apache Spark to support large-scale data modernization, migration, and analytics initiatives. The ideal candidate will have hands-on experience building high-performance data pipelines, optimizing large-scale data processing workloads, and integrating enterprise data platforms with modern cloud analytics solutions.
Key Responsibilities:

Design, develop, and optimize large-scale data processing solutions using Apache Spark (PySpark/Scala) and Python.
Build and maintain scalable ETL/ELT pipelines for analytical and reporting workloads.
Optimize query performance, Spark jobs, and end-to-end data processing pipelines for high-volume batch and near real-time workloads.
Design and implement data integration, replication, and ingestion solutions using technologies such as Oracle GoldenGate, Kafka, and CDC frameworks.
Collaborate with application, data, and analytics teams to develop scalable data models and processing frameworks.
Drive performance tuning initiatives across Oracle, Spark, and distributed data processing environments.

Required Qualifications:

8+ years of experience in Data Engineering or related roles.
Strong hands-on experience with Apache Spark (PySpark and/or Scala) and Python.
Deep understanding of Oracle databases supporting OLAP, data warehousing, and analytical workloads.
Proven experience tuning and optimizing:
Spark applications and execution plans
Complex SQL queries
Large-scale ETL/ELT processes
High-volume batch processing workloads
Strong SQL and data modeling skills.
Experience with Oracle GoldenGate, CDC, or enterprise-scale data integration technologies.

Preferred Qualifications:

Experience with Oracle Exadata and large-scale Oracle analytics platforms.
Experience with Google Cloud Platform (Google Cloud Platform) services such as BigQuery, Dataproc, Cloud Storage, Pub/Sub, and Dataflow.
Experience integrating Oracle with cloud data platforms, data lakes, Kafka, Hadoop, or BigQuery.
Experience with Azure, OCI, or multi-cloud data architectures.
Experience supporting large-scale data migration and modernization programs.
Ideal Candidate A hands-on data engineer with strong expertise in Oracle for analytical and data warehousing workloads, advanced Spark development and performance tuning skills, and experience building scalable cloud-based analytics solutions. Experience with Google Cloud and BigQuery is highly desirable.

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: 91116760
Position Id: 23d80c90ca2300f2db6dabc2ce59571f
Posted 10 hours ago

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