Senior Data Engineer

Job Summary

Seeking a Data Engineer with Spark & Streaming skills to build real-time, scalable data pipelines using tools like Spark, Kafka, and cloud services (GCP) to ingest, transform, and deliver data for analytics and ML.

• Design, develop, and maintain ETL/ELT data pipelines for batch and real-time data ingestion, transformation, and loading using Spark (PySpark/Scala) and streaming technologies (Kafka, Flink).
• Build and optimize scalable data architectures, including data lakes, data warehouses (Big Query), and streaming platforms.
• Optimize Spark jobs, SQL queries, and data processing workflows for speed, efficiency, and cost-effectiveness.
• Implement data quality checks, monitoring, and alerting systems to ensure data accuracy and consistency.

• Programming:
  Strong proficiency in Python, SQL, and potentially Scala/Java.
• Big Data:
  Expertise in Apache Spark (Spark SQL, Data Frames, Streaming).
• Streaming:
  Experience with messaging queues like Apache Kafka, or Pub/Sub.
• Cloud:
  Familiarity with GCP, Azure data services.
• Databases:
  Knowledge of data warehousing (Snowflake, Redshift) and No
  
  SQL databases.
• Total IT
  
  Experience:
  
  Minimum 8 years.
• GCP
  
  Experience:
  
  4+ years of recent GCP experience.

• Tools:
  Experience with Airflow, Databricks, Docker, Kubernetes.