PySpark Architect
1 week ago
As a PySpark Architect, you will be responsible for architecting, designing, and implementing large-scale data processing systems using PySpark.
- You will work closely with crossfunctional teams to develop robust, scalable, and efficient data solutions.
- Your deep experience in big data technologies and handson expertise in PySpark will be critical in driving our data initiatives forward.
Key Responsibilities :
Architectural Leadership :
- Lead the architecture, design, and implementation of largescale data processing applications using PySpark.
- Provide technical guidance and mentorship to development teams on best practices for data processing and PySpark development.
Solution Design and Development :
- Design and implement endtoend data pipelines to ingest, process, and analyze large volumes of data.
- Develop scalable and efficient PySpark applications to handle complex data transformations and aggregations.
- Ensure the solutions are designed for high availability, scalability, and performance.
Optimization and Performance Tuning :
- Optimize PySpark applications for performance and efficiency.
- Perform code reviews and provide recommendations for improvements.
- Identify and resolve performance bottlenecks in data processing workflows.
Collaboration and Stakeholder Management :
- Work closely with data engineers, data scientists, and other stakeholders to understand their requirements and translate them into technical solutions.
- Collaborate with infrastructure teams to ensure the deployment and scaling of data applications.
Documentation and Standards :
- Maintain comprehensive documentation of the architecture, design, and implementation details.
- Establish and enforce coding standards, best practices, and development methodologies.
Continuous Improvement :
- Stay updated with the latest trends and advancements in big data technologies.
- Identify opportunities for continuous improvement in data processing and analytics solutions.
Required Qualifications:
- Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
- 12 to 15 years of experience in software development with at least 5 years of experience in big data technologies.
- Extensive handson experience with PySpark and the Spark ecosystem.
- Strong expertise in designing and implementing largescale data processing systems.
- Proficiency in Python programming and related libraries for data processing.
- Solid understanding of distributed computing principles and big data architectures.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Strong knowledge of data warehousing and ETL processes.
- Excellent problemsolving and analytical skills.
- Strong communication and collaboration skills, with the ability to work effectively with crossfunctional teams.
Preferred Qualifications:
- Experience with additional big data technologies such as Hadoop, Hive, or Kafka.
- Knowledge of containerization and orchestration tools such as Docker and Kubernetes.
- Familiarity with data visualization tools and techniques.
- Certification in cloud platforms or big data technologies.
Job Location:
Chennai/Pune/Kolkata
)
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