PySpark Developer

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.
• 10+ years of IT experience with 6+ years in Data Engineering and Big Data development.
• Strong hands-on experience with PySpark and Spark-based data processing.
• Experience developing data pipelines on Cloudera Data Platform (CDP).
• Strong knowledge of Apache Iceberg table architecture and data lake concepts.
• Experience designing and managing workflows using Apache Airflow.
• Experience with SQL and data modeling techniques.
• Strong understanding of ETL/ELT development and data transformation frameworks.
• Experience working with large-scale structured and unstructured datasets.
• Knowledge of Git, CI/CD pipelines, and DevOps practices.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent communication and collaboration skills.

Preferred Qualifications

• Experience with AWS services including S3, Glue, Lambda, ECS/EKS, EMR, RDS, IAM, and CloudWatch.
• Experience building cloud-native data lake and Lakehouse solutions.
• Strong knowledge of data partitioning, performance tuning, and query optimization.
• Experience with Kafka or event-driven data processing frameworks.
• Experience with Java or Python application development.
• Experience implementing data quality, metadata, and data governance solutions.
• Healthcare, Medicaid, Claims Processing, or Insurance industry experience.
• Experience working in Agile development environments.
• AWS Certification and/or Cloudera Certification preferred.
• Experience supporting large-scale cloud migration and modernization initiatives.

Role Level: Senior Developer / Lead Developer

Experience: 10-12+ years overall with strong expertise in PySpark, Cloudera CDP, Apache Iceberg, Airflow, and AWS Data Engineering.