Data Engineer – Cloud & Big Data Platforms
KRYJAS PRIVATE LIMITED Toa Payoh
Key Responsibilities
Kafka, PySpark, AWS S3, Cloudera, and Azure Synapse
Data security/governance tools: Apache Ranger, Collibra, Protegrity
DevOps and orchestration: Azure DevOps, Airflow, Control-M
- Architect and implement scalable ETL/ELT data pipelines across cloud and hybrid environments using Azure Data Factory, Databricks, PySpark, and Kafka
- Build and maintain data lakes and lakehouse architectures aligned with enterprise security and governance requirements
- Ensure secure data processing using tools like Apache Ranger, Protegrity, and Collibra
- Support federated querying and metadata management through Trino, Starburst, and EDC tools
- Lead CI/CD automation for data workflows using Azure DevOps, Git, and related DevOps practices
- Act as SME for L2/L3 support, performance tuning, and audit readiness in production environments
- Collaborate with analytics, ML, and compliance teams to deliver ML-ready, governed datasets
- Minimum 8 years of relevant experience in data engineering
- At least 5 years working with data platforms in banking/regulated environments
- Deep technical expertise with:
Kafka, PySpark, AWS S3, Cloudera, and Azure Synapse
Data security/governance tools: Apache Ranger, Collibra, Protegrity
DevOps and orchestration: Azure DevOps, Airflow, Control-M
Programming & querying: Python, SQL, Trino/Presto
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