Verified Job
IT / Software / Data Analyst
Pyspark Developer
IT / Software / Data Analyst
#485603
Remote / WFH
Job Description
Overview
The Pyspark Developer plays a critical role in harnessing the power of big data to drive business insights and decisions. This position demands expertise in Pyspark, a Python API for Spark, to develop scalable and efficient data processing solutions. The developer will collaborate closely with data scientists, analysts, and other stakeholders to identify data requirements and align technical functionalities with business objectives. As organizations increasingly rely on data-driven strategies, the Pyspark Developer becomes essential for leveraging large datasets, transforming them into actionable information that enhances performance and innovation. Additionally, they must ensure that data pipelines are optimized, reliable, and maintainable. This role not only enhances the organization’s ability to process and analyze large amounts of data but also contributes to delivering meaningful insights that foster strategic initiatives. With the continuing growth in big data environments, this position is pivotal in achieving operational excellence and competitive advantage.
Key Responsibilities
• Design, develop, and maintain large-scale data processing systems using Pyspark.
• Collaborate with data engineers and analysts to define data pipeline requirements.
• Implement ETL processes for data ingestion and transformation.
• Optimize existing Pyspark applications for speed and efficiency.
• Conduct data profiling and analysis to ensure data quality.
• Integrate various data sources into a unified dataset for analysis.
• Utilize SparkSQL for advanced querying and analysis tasks.
• Develop and maintain documentation for data processing workflows.
• Monitor and troubleshoot performance issues within data pipelines.
• Work with cloud storage solutions, including AWS S3 and Azure Blob.
• Participate in code reviews to ensure code quality and adherence to best practices.
• Continuously evaluate new technologies and tools to improve data processing capabilities.
• Support data scientists in deploying models to production environments.
• Train and mentor junior developers on best practices in big data strategies.
• Provide support during data migrations and integrations projects.
Required Qualifications
• Bachelor’s degree in Computer Science, Information Technology, or related field.
• Proven experience in Pyspark and Apache Spark.
• Strong expertise in Python programming and data processing libraries.
• Knowledge of SQL and relational databases.
• Experience with ETL tools and data integration techniques.
• Familiarity with big data technologies such as Hadoop, Hive, and Kafka.
• Understanding of data warehousing concepts and architectural design.
• Proficiency in working with cloud platforms (AWS, Google Cloud, or Azure).
• Experience in data modeling and data architecture.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.
• Familiarity with version control systems, such as Git.
• Ability to work in a fast-paced, agile environment.
• Experience with data visualization tools is a plus.
• Prior experience in a similar role with a demonstrated ability to manage complex projects.
Skills: big data technologies,data warehousing,big data,data visualization,aws,hive,pyspark,sql,kafka,azure,data architecture,apache spark,scala,git,data modeling,analytical thinking,etl,data processing,hadoop,python,spark
The Pyspark Developer plays a critical role in harnessing the power of big data to drive business insights and decisions. This position demands expertise in Pyspark, a Python API for Spark, to develop scalable and efficient data processing solutions. The developer will collaborate closely with data scientists, analysts, and other stakeholders to identify data requirements and align technical functionalities with business objectives. As organizations increasingly rely on data-driven strategies, the Pyspark Developer becomes essential for leveraging large datasets, transforming them into actionable information that enhances performance and innovation. Additionally, they must ensure that data pipelines are optimized, reliable, and maintainable. This role not only enhances the organization’s ability to process and analyze large amounts of data but also contributes to delivering meaningful insights that foster strategic initiatives. With the continuing growth in big data environments, this position is pivotal in achieving operational excellence and competitive advantage.
Key Responsibilities
• Design, develop, and maintain large-scale data processing systems using Pyspark.
• Collaborate with data engineers and analysts to define data pipeline requirements.
• Implement ETL processes for data ingestion and transformation.
• Optimize existing Pyspark applications for speed and efficiency.
• Conduct data profiling and analysis to ensure data quality.
• Integrate various data sources into a unified dataset for analysis.
• Utilize SparkSQL for advanced querying and analysis tasks.
• Develop and maintain documentation for data processing workflows.
• Monitor and troubleshoot performance issues within data pipelines.
• Work with cloud storage solutions, including AWS S3 and Azure Blob.
• Participate in code reviews to ensure code quality and adherence to best practices.
• Continuously evaluate new technologies and tools to improve data processing capabilities.
• Support data scientists in deploying models to production environments.
• Train and mentor junior developers on best practices in big data strategies.
• Provide support during data migrations and integrations projects.
Required Qualifications
• Bachelor’s degree in Computer Science, Information Technology, or related field.
• Proven experience in Pyspark and Apache Spark.
• Strong expertise in Python programming and data processing libraries.
• Knowledge of SQL and relational databases.
• Experience with ETL tools and data integration techniques.
• Familiarity with big data technologies such as Hadoop, Hive, and Kafka.
• Understanding of data warehousing concepts and architectural design.
• Proficiency in working with cloud platforms (AWS, Google Cloud, or Azure).
• Experience in data modeling and data architecture.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.
• Familiarity with version control systems, such as Git.
• Ability to work in a fast-paced, agile environment.
• Experience with data visualization tools is a plus.
• Prior experience in a similar role with a demonstrated ability to manage complex projects.
Skills: big data technologies,data warehousing,big data,data visualization,aws,hive,pyspark,sql,kafka,azure,data architecture,apache spark,scala,git,data modeling,analytical thinking,etl,data processing,hadoop,python,spark
