PySpark Developer

1 week ago

bangalore, India Deloitte Full time
Deloitte India is hiring for PySpark Developer
Level: Deputy Manager
Location: Bangalore/Delhi NCR/Mumbai
Job Type: Full-time
Experience Required: 4-6 years
Job Summary:
We are seeking a talented and experienced Deputy Manager - PySpark Developer with 4 to 6 years of experience to join our dynamic team. The ideal candidate will possess extensive expertise in PySpark, big data technologies, and data engineering practices. As a Deputy Manager, you will play a critical role in developing and optimizing data processing pipelines, ensuring data quality, and collaborating with cross-functional teams to deliver high-impact data solutions.
Key Responsibilities:
PySpark Development:
Design, develop, and maintain scalable and efficient PySpark applications to process large datasets.
Write clean, maintainable, and efficient code following best practices and coding standards.
Optimize and tune PySpark jobs to improve performance and reduce execution times.
Big Data Technologies:
Work with big data tools and frameworks such as Hadoop, Hive, and Spark to manage and process large-scale data.
Implement and maintain data pipelines using Apache Airflow or similar orchestration tools.
Ensure data is ingested, processed, and stored in an optimal manner for further analysis and reporting.
Data Engineering:
Design and implement ETL processes to extract, transform, and load data from various sources.
Ensure data quality and consistency through robust validation and testing procedures.
Collaborate with data scientists and analysts to understand data requirements and deliver solutions that meet their needs.
Cloud Integration:
Deploy and manage big data solutions on cloud platforms such as AWS, Azure, or Google Cloud.
Leverage cloud services for storage, computing, and data processing to enhance scalability and performance.
Optimize cloud resource utilization to reduce costs and improve efficiency.
Collaboration and Communication:
Work closely with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand requirements and deliver data solutions.
Communicate effectively with team members and stakeholders, providing regular updates on project status.
Document technical designs, processes, and procedures to ensure knowledge sharing and continuity.
Continuous Improvement:
Stay up-to-date with the latest industry trends and technologies in big data and data engineering.
Identify opportunities for process improvement and implement best practices to enhance productivity and efficiency.
Participate in code reviews and provide constructive feedback to ensure code quality and maintainability.
Qualifications:
Bachelor's degree in Computer Science, Data Science, or a related field.
4-6 years of professional experience in PySpark development and big data technologies.
Strong understanding of distributed computing and parallel processing concepts.
Proficiency in SQL and experience with data warehousing solutions.
Familiarity with data modeling, ETL processes, and data pipeline orchestration.
Experience with cloud platforms (e.g., AWS, Azure, GCP) and related services.
Solid understanding of data structures, algorithms, and software engineering principles.
Excellent problem-solving skills and attention to detail.
Strong communication and interpersonal skills.
Preferred Qualifications:
Relevant certifications (e.g., Databricks Certified Associate Developer for Apache Spark).
Experience with real-time data processing and streaming technologies (e.g., Kafka, Flink).
Knowledge of machine learning frameworks and libraries.
Familiarity with containerization technologies (e.g., Docker, Kubernetes).
Experience with version control systems (e.g., Git).
How you’ll grow
Connect for impact
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Empower to lead
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Drive your career
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