Senior Data Engineer

Computer Task Group, Inc•UNAVAILABLE, UNAVAILABLE

10d•Remote

About The Position

CTG is seeking to fill a Senior Data Engineer position for our client. This is a remote, 12-month contract role. The Senior Data Engineer will be responsible for designing and implementing scalable data solutions using big data and cloud technologies, developing real-time data ingestion and processing solutions, building and maintaining ETL/ELT pipelines, developing data integration and migration strategies, designing and maintaining scalable data architectures, and ensuring data security, integrity, governance, and quality. The role also involves monitoring and troubleshooting data platform performance and managing data security, access controls, roles, permissions, encryption, and regulatory requirements. Collaboration with cross-functional teams to understand data requirements and deliver effective solutions is also a key part of the position.

Requirements

Python, PySpark, Kafka, and strong SQL.
GCP cloud data engineering technologies.
Snowflake and PostgreSQL preferred.
Data warehousing, data modeling, data governance, data quality, and data architecture.
ETL/ELT, real-time data processing, and large-scale structured/unstructured data.
CI/CD tools, including GitHub.
Scalable data architecture, cloud migration, and data integration.
5–9 years of professional data engineering experience.
Experience implementing databases and data warehouses.
Strong SQL skills, including writing and optimizing complex queries.
Hands-on experience with Python, PySpark, Kafka, and GCP.
Experience handling large-scale data from internal and third-party sources.
Experience designing, implementing, and maintaining scalable data platforms and architectures.
Bachelor’s degree in Engineering or Master’s degree in Computer Science, Information Systems, or a related field.
Excellent verbal and written English communication skills and the ability to interact professionally with a diverse group are required.

Responsibilities

Design and implement scalable data solutions using big data and cloud technologies, including Python, PySpark, and Kafka.
Develop real-time data ingestion and processing solutions.
Build and maintain ETL/ELT pipelines for analytics and reporting.
Develop data integration and migration strategies for transitioning legacy systems to the cloud.
Design and maintain scalable data architectures, data models, and data warehouse solutions.
Ensure data security, integrity, governance, and quality.
Monitor and troubleshoot data platform performance, availability, reliability, and scalability.
Manage data security, access controls, roles, permissions, encryption, and regulatory requirements.
Collaborate with cross-functional teams to understand data requirements and deliver effective solutions.