Data Engineer

Machine Learning Technologies, LLC; Irving (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Machine Learning Technologies, LLC in Irving, TX seeks an experienced Data Engineer to lead large-scale data modernization and analytics initiatives, focusing on Oracle-based analytical platforms and Apache Spark.

You will design and optimize end-to-end data pipelines using Spark (PySpark/Scala) and Python, build ETL/ELT processes, improve query performance, and implement data integration with Oracle GoldenGate, Kafka, and CDC.

Qualifications

• 8+ years of experience in Data Engineering or related roles.
• Hands-on experience with Apache Spark (PySpark and/or Scala) and Python.
• Deep understanding of Oracle databases for OLAP, data warehousing, and analytical workloads.
• Proven ability to tune Spark applications, complex SQL queries, and large-scale ETL/ELT processes.
• Strong SQL and data modeling skills.
• 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 and reporting workloads.
• Optimize query performance and Spark jobs for high-volume batch and near real-time workloads.
• Design and implement data integration using Oracle GoldenGate, Kafka, and CDC frameworks.
• Collaborate with application, data, and analytics teams to develop scalable data models and processing frameworks.
• Drive performance tuning across Oracle, Spark, and distributed data environments.

Skills

Spark

Python

SQL

Data modeling

ETL/ELT

Oracle databases

Tools

Oracle GoldenGate

Kafka

CDC frameworks

GCP (BigQuery/Dataproc)

Job description

We are seeking an experiencedData 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.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.