Back
Mid-level data engineer in Bangalore with common title and metro demand but requires GCP/Spark specialization.
GCP and Spark specialization requires cloud-data background, moderately limiting cross-industry transfers.
Explicit 6–8 years and mandatory GCP, Spark, BigQuery, and SQL expertise make filters strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, build, and optimize next-generation data architecture on Google Cloud Platform including BigQuery, Dataproc (Spark), Pub/Sub, and Dataflow.
Develop and maintain complex ETL/ELT data pipelines, managing large-scale Spark clusters and ensuring scalable, high-performance data warehousing.
Explore integration of Vertex AI and GenAI capabilities into production data pipelines to enhance data processing and AI workflows.
6 to 8 years of experience in senior software/data engineering roles.
Bachelor's degree in Computer Science or related field with at least 3 years of relevant experience.
Strong proficiency in Python or Scala programming and expertise in tuning/debugging Apache Spark jobs at scale.
Hands-on experience with Google Cloud data services including BigQuery, Dataflow, Dataproc, and Pub/Sub; advanced SQL skills required.
Experienced data engineer with a focus on large-scale data pipeline design and cloud-native (GCP) data architecture.
Skilled in optimizing Spark and BigQuery performance and operating in an environment leveraging real-time and batch streaming technologies.
Familiar with emerging AI/ML platforms such as Vertex AI and concepts around GenAI integration, supporting advanced data-driven AI use cases.