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Data Engineer

Cornerstone OnDemand · Hyderabad

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Collected role description

Role overview

Data Engineer at Cornerstone OnDemand

The role involves building reliable ETL/ELT pipelines, real-time data ingestion, data transformation, monitoring, and performance/cost optimization.

Responsibilities

  • Design and develop ETL/ELT data pipelines using AWS Glue, Databricks, and Spark.
  • Develop CDC-based data ingestion and event-driven data processing.
  • Develop and optimize data solutions on GCP, including BigQuery, Cloud Storage, Cloud Functions, and related services.
  • Implement secure data solutions using IAM, encryption, network controls, secrets management, and least-privilege access.

Employment details

  • Experience with cloud performance and cost optimization. #LI-Onsite
  • Location: Hyderabad [India]

Application details

  • Collaborate with application, DevOps, QA, analytics, and product teams to deliver reliable data solutions.

Additional role details

  • Data Engineer – Cloud & Big Data Role Summary: Responsible for designing, developing, and maintaining scalable cloud-based data pipelines and data platforms across AWS, GCP, Kafka, and Databricks.
  • In this role you will...
  • Build and maintain batch and real-time data pipelines using Apache Kafka / Confluent Kafka.
  • Work with AWS services including Glue, S3, Lambda, IAM, KMS, Secrets Manager, and related services.
  • Implement data processing using Databricks, PySpark, Delta Lake, Bronze/Silver/Gold architecture, and DLT.
  • Manage and optimize Elasticsearch/OpenSearch data ingestion, indexing, queries, and cluster performance.
  • Implement data quality, validation, monitoring, logging, and alerting across data pipelines.
  • Troubleshoot production issues involving Kafka, schema compatibility, CDC, Spark, Glue, Databricks, and cloud infrastructure.
  • Optimize pipeline performance and cloud infrastructure costs.
  • You've got what it takes if you have… 5+ years of experience in Data Engineering / Big Data Engineering.
  • Strong hands-on experience with AWS + Databricks + Kafka.
  • Experience working in multi-cloud environments (AWS/GCP).
  • Strong understanding of distributed systems, streaming, CDC, schema evolution, and data governance.
  • Experience troubleshooting high-volume production data pipelines.

Collected experience requirement

5+ years