
Senior Data Engineering Specialist
10 hours ago
This is a contract position seeking a highly motivated Data Engineer with experience in building, optimizing, and maintaining large-scale data processing solutions.
The ideal candidate will have strong knowledge of Spark, Hive, SQL, and Unix shell scripting, as well as experience with Databricks in a production environment and Azure cloud services. Additionally, they should have hands-on experience with Apache Kafka or other real-time streaming technologies and strong problem-solving skills.
Responsibilities- Design and develop data pipelines using Spark and Python to optimize data processing and scalability.
- Implement ETL/ELT solutions to integrate structured and unstructured data from multiple sources for seamless data transformations.
- Develop and maintain Hive queries to ensure efficient data extraction and processing.
- Write and optimize SQL queries for large datasets to improve performance and accuracy.
- Build, monitor, and support real-time streaming solutions using Apache Kafka to deliver timely insights.
- Work on Databricks to create, manage, and optimize data workflows for increased efficiency.
- Deploy and manage solutions in Azure cloud services to ensure scalability and reliability.
- Debug, troubleshoot, and optimize code for performance and scalability through collaboration with cross-functional teams.
- 3–4 years of experience in data engineering with a focus on PySpark and Python.
- Strong knowledge of Spark, Hive, SQL, and Unix shell scripting.
- Experience with Databricks in a production environment.
- Hands-on experience with Azure cloud services.
- Experience working with Apache Kafka or other real-time streaming technologies.
- Strong problem-solving and debugging skills.
- Excellent written and verbal communication skills.
This role offers opportunities for growth and professional development in a dynamic team environment.
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