Join our team as a Staff Engineer specializing in Data Engineering. This role involves designing, developing, and optimizing robust data pipelines and ETL processes. You will integrate diverse data sources, ensure data quality, and collaborate with stakeholders to deliver high-impact data solutions. We are looking for an experienced professional with a strong background in big data technologies and cloud platforms.

Key duties include architecting and maintaining scalable data pipelines using PySpark, integrating data from various sources to ensure quality and reliability, and optimizing data processing jobs for peak performance and cost-efficiency.

Further responsibilities involve developing comprehensive ETL processes, implementing rigorous data validation and monitoring, and documenting all data engineering workflows and best practices. You will also be responsible for swiftly identifying and resolving any data-related issues.

Candidates should possess over 3 years of experience in data engineering or a similar domain, holding a Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field. Proficiency in PySpark and Python is essential, alongside strong knowledge of big data technologies like Hadoop, Hive, and Spark.

Experience with cloud platforms (AWS, Azure, GCP) and their data services, familiarity with data warehousing solutions (Redshift, BigQuery, Snowflake), and knowledge of relational and NoSQL databases are required. Experience in ETL/ELT processes, data pipeline orchestration tools (Airflow, NiFi), and strong analytical, problem-solving, and communication skills are also vital for success in this role.