| Data Engineer with strong Python and Pyspark-- remote at Strong, Arkansas, USA |
| Email: [email protected] |
| From: Rishab, vkoresolutions [email protected] Reply to: [email protected] EDUCATION AND EXPERIENCE : Minimum of 5 years of experience in data engineering, with a focus on building and optimizing data pipelines. Expertise in Python programming and hands-on experience with PySpark for data processing and analysis. Proficiency in Python frameworks and libraries for scientific computing (e.g. Numpy, Pandas, SciPy, Pytorch, Pyarrow). Strong understanding of AWS services and experience in deploying data solutions on cloud platforms. Experience working with healthcare data, including but not limited to eligibility, claims, payments, and risk adjustment datasets. Expertise in modeling data in relational databases (e.g., PostgreSQL, MySQL) and file-based databases, ETL processes and data warehousing concepts. Proven track record of designing, implementing, and troubleshooting ETL processes and processing scripts using Python and PySpark. Excellent problem-solving skills and the ability to work independently as well as part of a team. Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field. Relevant certifications in AWS or data engineering would be a plus. OTHER DUTIES AND RESPONSIBILITIES Responsible for compliance with all federal, state, and local laws, rules and regulations affecting Company. Responsible for participating in quality assurance, compliance and in-service and continuing education activities as requested by Company. Responsible for performing other duties and responsibilities as required. Requirements Expertise in Python programming language for data processing and analysis. Expertise in PySpark for building scalable data pipelines. In-depth knowledge of AWS services such as S3, Glue, EMR, and Redshift for data storage and processing. Familiarity with relational databases (e.g., PostgreSQL, MySQL) and file-based databases for data modeling and storage. Understanding of data modeling, ETL processes, and data warehousing concepts. Knowledge of best practices in data engineering and experience in optimizing data workflows for performance and scalability. Experience in healthcare data domains, including eligibility, claims, payments, and risk adjustment datasets. Up-to-date knowledge of emerging technologies and trends in data engineering. Strong problem-solving skills and the ability to troubleshoot and optimize data pipelines and ETL processes. Excellent communication and collaboration skills to work effectively with cross-functional teams. Proficient in designing, implementing, and maintaining data pipelines for processing large volumes of data. Ability to model data in relational and file-based databases to support data processing requirements. Skill in developing monitoring and alerting mechanisms to ensure data quality and pipeline reliability. Experience in deploying data solutions on cloud platforms and utilizing AWS services for data processing. Proficiency in writing efficient and maintainable code for data processing tasks. Ability to stay organized, prioritize tasks, and meet project deadlines effectively. Ability to work independently and in a team-oriented, collaborative environment. Strong analytical skills to identify and address data quality issues and performance bottlenecks. Capability to innovate and recommend solutions for continuous improvement in data engineering processes. Ability to communicate complex technical concepts to non-technical stakeholders effectively. Strong attention to detail and commitment to delivering high-quality work. Ability to deal with problems involving several concrete variables in standardized situations. Ability to interact politely, tactfully and firmly with a wide range of people and personalities. Ability to work in an environment with potential interruptions. Ability to manage multiple simultaneous tasks with individual timeframes and priorities. Keywords: sthree Data Engineer with strong Python and Pyspark-- remote [email protected] |
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| Thu Apr 04 00:36:00 UTC 2024 |