Data Engineer

Must Have Skills - Data Engineer Skill 1 - big data, spark, pyspark, apache airflow, etl process Skill 2 - 4+ years in Google Cloud Platform Senior Data Engineer Description: We are seeking a Data Engineer with Spark & Streaming skills builds real-time, scalable data pipelines using tools like Spark, Kafka, and cloud services (Google Cloud Platform) 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-effectiveness Data 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 Google Cloud Platform, Azure data services. Databases: Knowledge of data warehousing (Snowflake, Redshift) and NoSQL databases. Tools: Experience with Airflow, Databricks, Docker, Kubernetes is a plus. Experience Level · Total IT Experience - Minimum 8 years · Google Cloud Platform - 4 + years of recent Google Cloud Platform experience