
Senior PySpark Developer
4 days ago
Join our team of expert data engineers and take on the challenge of working with large-scale data processing and analytics using PySpark.
As a PySpark Big Data Engineer, you will be responsible for designing, implementing, and optimizing efficient PySpark solutions for complex data processing tasks. You will work closely with cross-functional teams to understand business requirements and develop appropriate data solutions.
Some key responsibilities of this role include:
- Designing and implementing high-performance PySpark data pipelines to handle large-scale data processing and analysis.
- Developing and optimizing Spark SQL queries for big data analytics and reporting.
- Working with cloud platforms like AWS, Azure, or Google Cloud to deploy Spark-based applications and leverage cloud-native services for big data processing.
- Maintaining clear and comprehensive documentation of data pipelines, architectures, and processes to ensure knowledge sharing and continuity within the team.
Required qualifications for this role include:
- 2-4 years of professional experience working with PySpark and big data technologies.
- Strong expertise in Python programming with a focus on data processing and manipulation.
- Familiarity with cloud platforms like AWS, Azure, or Google Cloud, and experience with cloud-native big data tools.
- Knowledge of ETL processes and tools, as well as data storage technologies like HDFS, S3, or Google Cloud Storage.
- Experience with distributed computing and cluster management, including proficiency in Spark SQL for data querying and transformation.
We are looking for a skilled and experienced PySpark Big Data Engineer who is passionate about working with large-scale data processing and analytics. If you have a strong background in PySpark and big data technologies, and enjoy collaborating with cross-functional teams to drive business outcomes, we encourage you to apply for this exciting opportunity.
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