This role is for a highly skilled Data Architect with a robust background in big data technologies, especially PySpark, and significant experience in ETL processes. You will be instrumental in designing, implementing, and maintaining sophisticated data models to meet business demands and elevate our data analytics capabilities. This position requires a strategic approach to data architecture and a passion for optimizing data infrastructure.

Key duties involve designing, developing, and optimizing data models (conceptual, logical, physical) to ensure data integrity and performance. You will leverage PySpark for large-scale data processing and transformation, implementing and managing big data solutions on platforms like Hadoop, Spark, and Hive. Responsibilities also include developing, implementing, and maintaining efficient, scalable ETL processes, and collaborating with cross-functional teams to ensure seamless data integration. Performance tuning of data models and ETL processes is crucial for system optimization.

A Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field is required. Candidates should possess over 3 years of experience in data modeling and database design, alongside 3+ years of experience with big data technologies such as PySpark, Hadoop, Spark, and Hive. Proven experience with ETL tools and processes is essential. Proficiency in SQL, Python (especially PySpark), and familiarity with data warehousing solutions like Redshift or Snowflake are expected. Cloud platform experience (AWS, Azure, GCP) is a plus.