Join our team as a Staff Engineer specializing in Data Engineering. This role focuses on building and maintaining robust data infrastructure to support advanced analytics and machine learning initiatives. You will play a crucial part in shaping our data strategy and ensuring the quality and accessibility of our data assets.

We seek an experienced engineer to design, develop, and optimize scalable data pipelines. Your expertise will be vital in integrating diverse data sources, ensuring data integrity, and delivering high-performance data solutions. This is an excellent opportunity to contribute to a data-driven organization and tackle complex data challenges.

Key responsibilities include designing and implementing scalable data pipelines using PySpark to process vast amounts of data. You will integrate data from various sources, ensuring high quality and reliability, and optimize data processing jobs for performance and cost efficiency.

Further duties involve developing and maintaining ETL processes, implementing data validation and monitoring for accuracy, and documenting all data engineering workflows. You will also troubleshoot and resolve data-related issues promptly and collaborate with stakeholders to meet data requirements.

A minimum of 3 years of experience in data engineering or a similar domain is required. A Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field is necessary.

Essential technical skills include proficiency in PySpark and Python, strong knowledge of big data technologies like Hadoop, Hive, and Spark, and experience with cloud platforms such as AWS, Azure, or GCP. Familiarity with data warehousing solutions and databases (SQL/NoSQL) is also expected, alongside experience in ETL/ELT processes and orchestration tools. Excellent problem-solving and communication abilities are paramount.