We are looking for a talented Data Engineer to join our team. This role requires a passion for building scalable data pipelines, working with cloud technologies, and ensuring high-quality data processing.
Key Responsibilities
Design, build, and maintain efficient data pipelines using PySpark and AWS technologies.
Develop and optimize ETL processes to support data transformation, integration, and loading into data warehouses or lakes.
Write high-quality, reusable, and maintainable Python code for data processing tasks.
Ensure the consistency, reliability, and scalability of the data infrastructure on AWS.
Develop and execute complex SQL queries for data extraction, manipulation, and analysis.
Monitor, troubleshoot, and optimize existing data workflows for performance improvements.
Work with Big Data technologies such as Apache Spark, AWS Glue, and Redshift.
Implement data quality and validation checks to ensure data integrity.
Required Skills And Experience
2+ years of experience designing, developing, and maintaining scalable data pipelines using PySpark.
Expertise in Data Transformation using PySpark.
Strong proficiency in Python and experience in using it for data engineering tasks.
Hands-on experience with PySpark for distributed data processing.
Develop, deploy, and maintain data solutions on AWS, ensuring scalability, security, and high availability.
Strong knowledge of SQL and experience writing complex queries for data extraction and transformation.
Experience building and maintaining ETL pipelines and data integration workflows.
Experience with data warehousing concepts and working with cloud data platforms.
Preferred Skills
Basic Knowledge of PowerBi.
Excellent communication skills.
Qualifications
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
Strong problem-solving skills and attention to detail.
Excellent communication and teamwork skills.
(ref:hirist.tech)
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