Senior Data Engineering
Tasks
- Build data models and data marts
- Build datasets for AI and machine learning initiatives
- Create technical documentation and runbooks
- Design batch streaming and near real time data pipelines
- Develop enterprise data platforms
- Ensure PCI-DSS and privacy compliance
- Evaluate emerging technologies and improve data strategy
- Implement ETL/ELT frameworks
- Implement data governance and lineage tracking
- Implement encryption tokenization masking and secure handling
- Integrate and govern data sources
- Mentor junior data engineers
- Monitor and tune pipeline and platform performance
- Monitor reliability with Splunk and Dynatrace
- Orchestrate workflows with scheduling and automation
- Perform incident management and root cause analysis
- Process large scale datasets with Spark
- Provide disaster recovery and operational support
- Support secure file transfer and integrations
Perks/Benefits
- N/A
Skills/Tech-stack
Apache Airflow | Apache NiFi | Apache Spark | Azure Cloud | Azure Cloud Services | Azure Data | Azure Data Factory | CI/CD | Cause analysis | Cloud services | Data Factory | Data Governance | Data Lineage | Data Modeling | Data Quality | Data Warehousing | Data masking | Databricks | DevOps | Dimensional Modeling | Disaster Recovery | Disaster Recovery Planning | Dynatrace | ELT | ETL | Encryption | File Transfer | Incident Management | Infrastructure as Code | Key Management | Managed File Transfer | Metadata Management | PCI DSS | PII | Python | Recovery Planning | Root Cause Analysis | Root cause | SFTP | SQL | Snowflake | Splunk | Terraform | Tokenization | “as-code”
Education
Roles
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