Data Engineer

TheCorporate; Tulsa (OK); On-site; USD 110,000 - 150,000; Full time

Benefits offered by this job

Cutting-edge data technologies

Collaborative culture

Competitive compensation

Job summary

TheCorporate is seeking a Data Engineer to design and maintain scalable data pipelines and architectures in Tulsa. You will work with analysts and scientists to enable advanced analytics and reporting, while optimizing data flows for performance in both cloud and on-premise environments.

Responsibilities include building data models, implementing ETL processes, ensuring data integrity and security, and monitoring systems to implement reliability improvements.

Qualifications

• Proficiency in Python and SQL.
• Experience with Spark, Kafka, and other big data technologies.
• Hands-on experience with cloud platforms, preferably AWS.
• Strong understanding of ETL pipeline development and data warehousing concepts.
• Excellent problem-solving and communication skills.

Responsibilities

• Design, develop, and maintain scalable data pipelines and architectures to support analytical and operational processes.
• Collaborate with data analysts and scientists to implement data solutions that enable advanced analytics and reporting.
• Optimize data flows and queries for high performance and efficiency across cloud and on-premise environments.
• Build and manage data models, data sets, and repositories ensuring data integrity and security.
• Implement ETL processes using modern tools and frameworks to automate data ingestion and transformation.
• Monitor system performance, troubleshoot issues, and implement improvements to enhance reliability.

Skills

Python

SQL

Spark

Kafka

AWS

ETL

Data warehousing

Problem solving

Communication

Tools

Docker

Kubernetes

Job description

Role & Responsibilities

• Design, develop, and maintain scalable data pipelines and architectures to support analytical and operational processes.
• Collaborate with data analysts and scientists to implement data solutions that enable advanced analytics and reporting.
• Optimize data flows and queries for high performance and efficiency across cloud and on-premise environments.
• Build and manage data models, data sets, and repositories ensuring data integrity and security.
• Implement ETL processes using modern tools and frameworks to automate data ingestion and transformation.
• Monitor system performance, troubleshoot issues, and implement improvements to enhance reliability.

Skills & Qualifications

Must-Have Skills

• Proficiency in Python and SQL
• Experience with Spark, Kafka, and other big data technologies
• Hands-on experience with cloud platforms, preferably AWS
• Strong understanding of ETL pipeline development and data warehousing concepts
• Excellent problem-solving and communication skills

Preferred Skills

• Knowledge of data governance and security practices
• Experience with containerization tools like Docker or Kubernetes
• Familiarity with machine learning data workflows

Benefits & Culture Highlights

• Opportunity to work with cutting-edge data technologies in a collaborative environment
• Supportive culture fostering innovation and continuous learning
• Competitive compensation and benefits package