Senior Analyst-Data Management - PySpark Job Description Template
As a Senior Analyst-Data Management - PySpark, you will be instrumental in managing, processing, and analyzing large datasets to support business goals. You will design and implement efficient data pipelines using PySpark and work closely with various stakeholders to ensure data quality and integrity.
Responsibilities
- Design and implement efficient data pipelines using PySpark.
- Manage and process large-scale datasets to support analytics and business intelligence.
- Conduct complex analyses and provide insights to drive data-driven decision-making.
- Ensure the quality, integrity, and security of data throughout the data lifecycle.
- Collaborate with cross-functional teams to understand data requirements and deliver solutions.
- Optimize and troubleshoot data processing workflows to improve performance.
Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Information Technology, or a related field.
- 5+ years of experience in data management, data engineering, or a similar role.
- Strong expertise in PySpark and large-scale data processing.
- Proven experience with data pipeline architectures and ETL processes.
- Familiarity with data warehousing concepts and technologies.
- Excellent problem-solving skills and attention to detail.
Skills
- PySpark
- SQL
- Apache Spark
- ETL processes
- Data warehousing
- Python
- Big Data technologies
- Data analysis
- Data modeling
- Cloud platforms (AWS, Azure, GCP)
Frequently Asked Questions
A Senior Analyst-Data Management specializing in PySpark is responsible for designing and implementing data processing solutions using PySpark, a Python API for Spark. This role involves handling large datasets, optimizing data pipelines, and ensuring high-quality data management. They work closely with data engineers and scientists to support big data solutions, troubleshoot data-related issues, and improve data-driven decision-making.
To become a Senior Analyst-Data Management with expertise in PySpark, one should pursue a degree in Computer Science, Data Science, or a related field, followed by gaining experience in big data technologies. Proficiency in programming languages like Python and familiarity with Apache Spark are crucial. Obtaining certifications in data management and big data analytics can further enhance your profile for this role.
The typical salary for a Senior Analyst-Data Management with PySpark skills varies depending on factors like location, industry, and experience. Generally, professionals in this role can expect a competitive salary range, reflective of their expertise in handling big data solutions. Additional factors such as certifications and advanced proficiency in PySpark could positively influence compensation.
Qualifications for a Senior Analyst-Data Management role using PySpark include a bachelor's or master's degree in a relevant field, extensive experience with big data tools like Apache Spark, and strong programming skills, particularly in Python. Candidates should also possess data modeling expertise, proficiency in data analysis, and problem-solving abilities to succeed in this role.
A Senior Analyst-Data Management focusing on PySpark should possess skills in data processing, proficiency with PySpark and Python, and experience in data pipeline development. Key responsibilities include managing and optimizing large datasets, ensuring data integrity, and collaborating with cross-functional teams to enhance data-driven processes. Strong analytical and communication skills are also important for this role.