포지션 소개
- Strong hands-on GCP Data Engineering experience across scalable cloud data platforms.
- Expertise in Google Cloud Storage, Big Query, 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, Py Spark 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.
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 Big Query, Cloud Storage, Dataflow, Pub/Sub, Dataproc, Python, Py Spark 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 Big Query 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.
- GCP Big Query, 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 Big Query, Cloud Storage, Dataflow, Pub/Sub, Dataproc, Python, Py Spark 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 Big Query 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.
Infosys is a global leader in next-generation digital services and consulting. Within the Data & Analytics unit, you will work on cutting-edge data engineering and analytics initiatives for global clients across industries. The role offers opportunities to work with cloud-native data platforms, modern analytics ecosystems, AI-driven solutions, and large-scale enterprise data modernization programs. Employees benefit from continuous learning programs, certifications, and career growth opportunities within Infosys' data and analytics practice
Education: Master Of Comp. Applications,Master Of Technology,Bachelor Of Science,Bachelor of Engineering,Bachelor Of Technology
Preferred skills: Technology->Cloud Platform->GCP Database
