Director, Data Engineering
Purchase, New York, United States
USD 195K-323K Executive-level Full Time
Tasks
- Create documentation standards and best practices for self service adoption
- Define and govern data schemas contracts and transformations
- Design enterprise data platform architecture
- Drive data quality monitoring alerting and SLA management
- Enable scalable repeatable data foundations for downstream teams
- Ensure data pipelines meet security privacy and governance requirements for AI
- Ensure data platform performance scalability reliability and cost optimization
- Establish CI CD automation and infrastructure as code practices
- Integrate data platform with AI enabled use cases and workflows
- Lead enterprise data platform strategy and roadmap
- Lead operational readiness for batch and near real time processing incident management and root cause analysis
- Lead platform modernization capacity planning and cloud migration
- Manage object storage data layout lifecycle and retention policies
- Mentor and lead engineering managers and technical leaders
- Own end to end data pipeline ingestion processing and orchestration
- Partner with DevOps SRE and infrastructure teams for observability and resiliency
- Provide architectural oversight for Kubernetes deployed data workloads
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Amazon S3 | Apache Airflow | Apache Kafka | Apache NiFi | Apache Spark | Azure | CI/CD | Cloud platform | Data Governance | Data Modeling | Data Quality | Data Reliability | Delta Lake | Elasticsearch | Google Cloud | Google Cloud Platform | Grafana | Hudi | Iceberg | Infrastructure as Code | Kafka Streams | Kibana | Kubernetes | Logstash | Object storage | PII Detection | Parquet | Prometheus | Schema evolution | “as-code”
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