
High Performance Data Architect
3 days ago
Our organization seeks an accomplished Senior Data Engineer to lead the development and implementation of large-scale data processing systems.
The ideal candidate will have a strong background in designing, building, and maintaining high-performance data solutions using Hadoop ecosystem, Spark, and other distributed frameworks.
- Design, develop, and maintain scalable Big Data solutions.
- Build and optimize data pipelines for batch and real-time data processing.
- Collaborate with data scientists, analysts, and developers to integrate data-driven solutions into production.
- Write efficient, testable, and reusable code using Java or Python.
- Work closely with DevOps teams to deploy and monitor applications on cloud/on-prem infrastructure.
- Ensure data integrity, security, and performance tuning of large-scale data systems.
Key Requirements:
- Strong programming skills in Java or Python.
- Hands-on experience with Big Data technologies such as Hadoop, Hive, HDFS, Spark, Kafka, etc.
- Familiarity with data modeling, ETL pipelines, and data warehousing concepts.
- Good understanding of SQL and NoSQL databases.
- Experience with cloud platforms such as AWS, GCP, or Azure is desirable.
- Knowledge of CI/CD tools and containerization (Docker/Kubernetes) is advantageous.
Required Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Minimum 5 years of experience in Big Data development with strong coding background in Java or Python.
- Strong problem-solving skills and ability to work independently or in a team.
- Excellent communication and collaboration skills.
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