GCP Data Engineer

Infosys · Bangalore, India · 1-3 years · Full-time

Key skills

Strong hands-on GCP Data Engineering experience across scalable cloud data platforms.
Expertise in Google Cloud Storage, BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Cloud Functions, Cloud Monitoring, IAM and Secret Manager.
Strong experience in batch and real-time streaming using Pub/Sub, Dataflow / Apache Beam, Spark Structured Streaming or Kafka.
Hands-on coding proficiency in Python, PySpark and SQL, including debugging and performance optimization.
Experience building high-volume, low-latency ingestion and transformation pipelines with retry, idempotency, deduplication and dead-letter handling.
Strong experience in Databricks, Delta Lake, Structured Streaming, Auto Loader and Spark performance tuning.
Experience handling TB/PB-scale datasets, partitioning, clustering, file compaction, schema evolution and data lifecycle management.
Strong understanding of Data Lake, Lakehouse and modern cloud data-platform architectures.
Practical data-modeling experience for analytics, reporting and downstream consumption.
Experience implementing CI/CD using Cloud Build, GitHub Actions, Jenkins or equivalent, with Terraform for Infrastructure as Code.
Strong troubleshooting, observability, production support and cloud cost-optimization skills.
Excellent client communication, stakeholder management and problem-solving skills.

Technical Requirements:

GCP BigQuery, Cloud Storage, Dataflow, Pub/Sub, Dataproc, batch and real-time streaming, Databricks , Pyspark
Python, strong SQL

Databricks with Delta Lake and Structured Streaming

Responsibilities and JD in brief along with additional criteria to be considered:

Design and develop scalable GCP Data Engineering solutions and cloud-native data platforms.
Build batch and real-time pipelines using BigQuery, Cloud Storage, Dataflow, Pub/Sub, Dataproc, Python, PySpark and Databricks.
Develop and optimize Databricks, Delta Lake, Spark and Structured Streaming workloads for large-scale processing.
Implement high-throughput streaming solutions using Pub/Sub and Dataflow, including windowing, watermarking, late-arriving data, duplicate handling and dead-letter queues.
Handle high-volume TB/PB-scale data with focus on performance, scalability, reliability and cost optimization.
Develop complex SQL transformations, data models and analytics-ready BigQuery datasets using partitioning and clustering.
Orchestrate pipelines using Cloud Composer / Airflow and implement CI/CD and Terraform-based Infrastructure as Code.
Ensure data quality, governance, security, monitoring, alerting and production support.
Collaborate with architects, stakeholders and cross-functional teams in an Agile delivery model.
Troubleshoot and optimize end-to-end GCP, Databricks and streaming data pipelines.

Responsibilities:

Responsibilities and JD in brief along with additional criteria to be considered:

Design and develop scalable GCP Data Engineering solutions and cloud-native data platforms.
Build batch and real-time pipelines using BigQuery, Cloud Storage, Dataflow, Pub/Sub, Dataproc, Python, PySpark and Databricks.
Develop and optimize Databricks, Delta Lake, Spark and Structured Streaming workloads for large-scale processing.
Implement high-throughput streaming solutions using Pub/Sub and Dataflow, including windowing, watermarking, late-arriving data, duplicate handling and dead-letter queues.
Handle high-volume TB/PB-scale data with focus on performance, scalability, reliability and cost optimization.
Develop complex SQL transformations, data models and analytics-ready BigQuery datasets using partitioning and clustering.
Orchestrate pipelines using Cloud Composer / Airflow and implement CI/CD and Terraform-based Infrastructure as Code.
Ensure data quality, governance, security, monitoring, alerting and production support.
Collaborate with architects, stakeholders and cross-functional teams in an Agile delivery model.
Troubleshoot and optimize end-to-end GCP, Databricks and streaming data pipelines.

Preferred Skills:

Technology->Cloud Platform->GCP Database