Senior Oracle Data Engineer & ETL Lead - Onsite Charlotte

RaceDog Technologies; Charlotte (NC); On-site; USD 140,000 - 190,000; Full time

Job summary

RaceDog Technologies seeks a Lead Data Engineer to lead enterprise data warehousing, ETL, and Oracle RDBMS optimization in Charlotte, NC. This on-site role requires 12+ years in data engineering and a proven track record architecting robust data pipelines and scalable data models.

You will mentor engineers, set coding standards, partner with data scientists and analysts, and drive performance tuning, data quality, and governance across critical data stores.

Qualifications

• 12+ years of professional data engineering experience in complex enterprise environments.
• Deep expertise in Oracle RDBMS architecture, database administration, and performance tuning.
• Mandatory advanced technical proficiency in SQL and PL/SQL programming for complex data transformations.

Responsibilities

• Lead design of scalable ETL pipelines and data warehouses.
• Optimize Oracle environments, schemas, and partitioning strategies.
• Develop and tune complex SQL queries and PL/SQL packages for max speed.
• Ensure data quality, lineage, governance, validation, and integrity across data stores.
• Collaborate with data scientists, BI analysts, and developers for analytics and reporting.
• Mentor junior engineers and establish architectural best practices.
• Create data architecture blueprints, ETL runbooks, and schema diagrams.

Skills

Oracle RDBMS

SQL

PL/SQL

ETL pipelines

Informatica

Talend

Apache Airflow

Cloud storage

Data modeling

Performance tuning

Education

Bachelor’s degree in Computer Science or related field

Tools

Informatica

Talend

Apache Airflow

Oracle RDBMS

Job description

RaceDog Technologies seeks a Lead Data Engineer to lead enterprise data warehousing, ETL, and Oracle RDBMS optimization in Charlotte, NC. This on-site role requires 12+ years in data engineering and a proven track record architecting robust data pipelines and scalable data models.

You will mentor engineers, set coding standards, partner with data scientists and analysts, and drive performance tuning, data quality, and governance across critical data stores.