Sr. Data Engineer

TEKsystems•Charlotte, NC

4d•$65 - $65•Hybrid

About The Position

This is a contract position for a Sr. Data Engineer with expertise in Oracle/SQL development. The role involves leading and mentoring Oracle developers, designing and supporting data integration workflows, and driving the migration of data from ServiceNow into enterprise data platforms. The engineer will evaluate and implement integration patterns, develop complex SQL queries, analyze schemas, map data, identify data quality issues, optimize query performance, and define transformation strategies. The position requires partnering with stakeholders to understand data requirements and establishing resilient data processing solutions with error handling. Support for source control and deployment best practices using Bitbucket and Git is also expected.

Requirements

Oracle
SQL
ETL
Python
Spark
Oracle Exadata
Autosys
Expert Level experience

Nice To Haves

Experience with ServiceNow data migration and integration.
Familiarity with SSIS packages.
Knowledge of APIs, database links, and other data ingestion methods.
Experience with Bitbucket and Git for source control and deployment.

Responsibilities

Lead and mentor Oracle developers while providing technical guidance and best practices for data integration and ETL development.
Design, build, and support SSIS packages and data integration workflows across enterprise systems.
Drive the migration and integration of data from ServiceNow into existing enterprise data platforms and reporting structures.
Evaluate and implement the most effective integration patterns, including APIs, database links, and other data ingestion methods.
Develop complex Oracle SQL queries to extract, transform, and load data from multiple source systems.
Analyze source system schemas and map data into existing enterprise data models and downstream reporting layers.
Identify data mapping gaps and data quality issues between legacy and target systems, ensuring accurate reconciliation of data.
Optimize query performance, execution plans, and data processing workflows to improve scalability and reliability.
Define and implement efficient transformation strategies within ETL pipelines.
Partner with business and technical stakeholders to understand data requirements and integration needs.
Establish resilient data processing solutions with appropriate error handling, recovery, and fallback mechanisms.
Support source control and deployment best practices using tools such as Bitbucket and Git.