Data Engineer With Spark & ScalaWe are seeking a Data Engineer with Spark & SCALA; Streaming skills builds real-time, scalable data pipelines using tools like Spark, Kafka, and cloud services (GCP) to ingest, transform, and deliver data for analytics and ML.Responsibilities:As a Senior Data Engineer, you will 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 (BigQuery), and streaming platforms.Performance Tuning: Optimize Spark jobs, SQL queries, and data processing workflows for speed, efficiency, and cost-effectivenessData Quality: Implement data quality checks, monitoring, and alerting systems to ensure data accuracy and consistency.Required Skills & Qualifications:Programming: Strong proficiency in Python, SQL, and potentially Scala/Java.Big Data: Expertise in Apache Spark (Spark SQL, DataFrames, 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 NoSQL databases.Tools: Experience with Airflow, Databricks, Docker, Kubernetes is a plus.