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# Senior Data Engineer

- **Company:** Computer Task Group, Inc
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $145,600.0 - $158,080.0
- **Contract:** Temporary contract
- **Skills:** Big Data, Cloud Computing, Cloud Database, Information Systems, Databases, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Security, Data Warehousing, Database Queries, Github, Python (Programming Language), PostgreSQL, Unstructured Data, Google Cloud, Snowflake, Pyspark, Information Technology, Real Time Data, Apache Kafka, Data Management, Cloud Migration, Stream Processing, Data Pipelines, Legacy Systems
- **Published:** October 2, 2026
- **Apply:** https://www.dice.com/job-detail/3f0b71b8-1991-4d41-a5c4-2d7400a9e14d

## About the Role

* Python, PySpark, Kafka, and strong SQL.
 * Google Cloud Platform 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.

Experience:

 * 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 Google Cloud Platform.
 * Experience handling large-scale data from internal and third-party sources.
 * Experience designing, implementing, and maintaining scalable data platforms and architectures.

Education:

 * 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.

## Description

* 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.


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