Google Cloud Platform Data Engineer

Design, develop, and maintain scalable ETL/ELT data pipelines for batch and real-time processing.

Build and manage real-time streaming solutions using Apache Kafka and similar technologies.

Develop high-performance data workflows using Apache Spark (PySpark/Scala) and Structured Streaming.

Architect and maintain modern data platforms including data lakes and data warehouses.

Optimize Spark jobs, SQL queries, and streaming workloads for performance and cost efficiency.

Implement data quality checks, monitoring systems, and automated alerting processes.

Work with Google Cloud Platform (Google Cloud Platform) services such as BigQuery, Dataflow, Pub/Sub, and Dataproc.

Collaborate with Data Science, Analytics, and Product teams to support analytics and ML use cases.

Deploy and manage data solutions using Docker and Kubernetes.

Maintain technical documentation and enforce data governance standards.

Develop solutions using Python, SQL, and working knowledge of Scala or Java.

Support enterprise-level data warehousing solutions such as BigQuery, Snowflake, or Redshift.

Utilize messaging and streaming platforms like Apache Kafka or Google Pub/Sub.

Ensure scalable, reliable, and low-latency data architecture.

Deliver production-ready data platforms with a strong focus on reliability and scalability.

Bring 8+ years of experience in enterprise data engineering solutions.

Possess 4+ years of hands-on experience with Google Cloud Platform data services.