Join our team as a Staff Data Engineer and play a pivotal role in shaping our data landscape. This position offers a dynamic environment to design, develop, and optimize robust data solutions that drive business insights. You will work with cutting-edge big data technologies and cloud platforms.

This role is for an experienced professional passionate about building scalable and efficient data infrastructure. If you excel in problem-solving and collaborating with diverse teams, we encourage you to apply.

Key contributions include architecting and implementing scalable data pipelines using PySpark for processing vast datasets from multiple origins. You will integrate diverse data sources, ensuring superior data quality and reliability. Optimizing data processing jobs for peak performance and cost-effectiveness is also a core responsibility.

Furthermore, you will collaborate closely with data scientists and analysts to translate data requirements into actionable solutions. Developing and maintaining ETL/ELT processes for data warehousing and data lakes, alongside implementing data validation and monitoring systems, will be crucial. Clear documentation of processes and timely troubleshooting of data issues are also expected.

A Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related discipline is required. We are looking for candidates with a minimum of 3 years of hands-on experience in data engineering or a comparable role.

Essential technical skills include advanced proficiency in PySpark and Python. Strong expertise in big data technologies such as Hadoop, Hive, and Spark is vital. Experience with major cloud platforms like AWS, Azure, or GCP and their associated data services is essential. Familiarity with data warehousing solutions and both relational and NoSQL databases is also necessary.