Data Engineer

Cornerstone OnDemand • Learning Management Systems • HR & Payroll Software • Python • ETL/ELT • AWS Glue • 3 days ago
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Salary
≈ $21k – $43k per year (Estimated)
Location
In office (Hyderabad)
Seniority
Senior · 5+ years exp

Confirmed on the employer's own hiring board on Oct 24, 2026. First seen by Alion on Oct 21, 2026. Cornerstone OnDemand scores B on the Alion truth index.

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Cornerstone OnDemand

Cornerstone OnDemand is a Santa Monica, California software company that sells a cloud platform for workforce readiness, covering learning, talent development, skills intelligence and compliance training with AI agents. Founded in 1999 and taken private by Clearlake Capital in 2021, it serves employers worldwide and runs large engineering and support hubs in Hyderabad and Pune in India, Krakow in Poland and Heredia in Costa Rica. It hires AI engineers and scientists, forward deployment and solution engineers, SDETs, technical consultants, product support engineers, instructional designers and sales staff.
cornerstoneondemand.com • HQ: Santa Monica, United States • Learning Management Systems • HR & Payroll Software • 1001-5000 employees • Est. 1999
Tech stack of Cornerstone OnDemand
Backed by Bessemer Venture Partners, Vista Equity Partners, Bright Pixel Capital

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

Design and develop ETL/ELT data pipelines using AWS Glue, Databricks, and Spark. Build and maintain batch and real-time data pipelines using Apache Kafka / Confluent Kafka. Develop CDC-based data ingestion and event-driven data processing.

Work with AWS services including Glue, S3, Lambda, IAM, KMS, Secrets Manager, and related services. Develop and optimize data solutions on GCP, including BigQuery, Cloud Storage, Cloud Functions, 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. Implement secure data solutions using IAM, encryption, network controls, secrets management, and least-privilege access. Collaborate with application, DevOps, QA, analytics, and product teams to deliver reliable data solutions.

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. Experience with cloud performance and cost optimization. #LI-Onsite

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