Senior Data Engineer Oracle, Spark & Cloud Analytics

JobDiva, Inc.; Charlotte (NC); On-site; USD 120,000 - 170,000; Full time

Job summary

JobDiva, Inc. in Charlotte, NC is seeking a Senior Data Engineer with Oracle OLAP and Spark expertise to lead large-scale data modernization and analytics initiatives.

You will build high-performance data pipelines with PySpark/Scala, optimize SQL and Spark workloads, and design data models for cloud analytics platforms. This role requires 8+ years in data engineering and hands-on Oracle GoldenGate, Kafka, and CDC experience.

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 Spark applications, SQL queries, and large-scale ETL/ELT processes.
• Experience with Oracle GoldenGate, CDC, or enterprise-scale data integration technologies.

Responsibilities

• Design, develop, and optimize large-scale data processing solutions using Spark (PySpark/Scala) and Python.
• Build and maintain scalable ETL/ELT pipelines for analytical workloads.
• Optimize query performance, Spark jobs, and end-to-end data pipelines for high-volume workloads.
• Design and implement data integration, replication, and ingestion using Oracle GoldenGate, Kafka, and CDC frameworks.
• Collaborate with cross-functional teams to develop scalable data models and processing frameworks.
• Drive performance tuning across Oracle, Spark, and distributed data environments.

Skills

PySpark

Scala

Python

SQL

Data Modeling

ETL/ELT

Performance Tuning

Tools

Oracle GoldenGate

Kafka

CDC

Oracle DB

BigQuery

Dataproc

Job description

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 (GCP) 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.