What you need:

- 7–12 years of relevant experience in Data Engineering, with strong hands-on expertise in Apache Spark and Scala.
- Strong experience with GCP services, particularly Dataproc, BigQuery and Google Cloud Storage (GCS).
- Solid SQL skills, particularly BigQuery SQL, for data transformation, validation and reconciliation.
- Hands-on experience with large-scale ETL pipelines, distributed data processing, Hive, Kafka and high-volume batch/streaming workloads.
- Strong Unix/Linux shell scripting skills for automation, data movement and pipeline orchestration, along with familiarity with Git, Jenkins and CI/CD.
- Strong understanding of data modelling, data quality, distributed systems and performance optimisation, with the ability to independently troubleshoot complex issues and deliver solutions with minimal handholding.

What you would do:

- Design, develop and optimise large-scale data pipelines using Apache Spark and Scala across high-volume batch and streaming workloads.




- Build and support data processing solutions using Hive, Kafka, BigQuery, Dataproc and GCS across multiple data sources.
- Develop, maintain and optimise ETL workflows, data orchestration pipelines and engineering automation using shell scripting and relevant tools.
- Troubleshoot complex data, performance and production issues; perform Spark job tuning and optimise processing across large datasets.
- Drive cloud migration, data migration and platform modernisation initiatives, including workload migration, data reconciliation and validation.
- Take end-to-end ownership of assigned deliverables, from understanding existing systems and solution development through testing, code reviews, CI/CD deployments and production support, collaborating with cross-functional teams.

📌 Senior Data Engineer (Spark, Scala) | 9 to 13 YoE | US-based large retail organisation | Bengaluru | Immediate/Early joiners
🏢 Geektrust
📍 Bengaluru