Senior Full Stack Engineer

Strong hands-on experience in Python, leveraging PySpark, Scikit-learn, TensorFlow, PyTorch, Pandas, PyArrow, and related tools for large-scale data transformation and automation

Design, develop, and optimize distributed data pipelines using Apache Spark (PySpark)

Deploy and manage Spark workloads on AWS EMR (cluster sizing, autoscaling, performance tuning)

Implement centralized data governance and analytics solutions on AWS, including AWS Glue Data Catalog, EMR, Athena, and Glue Jobs

Develop ETL/ELT workflows using AWS Glue (Glue Jobs, Crawlers, Data Catalog)

Orchestrate data workflows using Step Functions, Airflow, or Glue Workflows

Strong understanding of business-layer modeling, data architecture, and batch/real-time data processing

Hands-on with AWS services: EC2, S3, CloudFront, API Gateway, Lambda, RDS/PostgreSQL, IAM roles

Kubernetes (EKS, Helm) and containerized application management

Experience developing SPA using Angular with TypeScript or comparable JS frameworks

Optional: DevOps tools (Git, GitLab, CloudFormation, Terraform), Docker, Kafka streaming pipelines, Delta Lake/Iceberg/Hud