Databricks Forward Deployed Engineer
Skills
DevopsAgility TrainingApache SparkCost EngineeringEasily AdaptableHeavy EquipmentManagement
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 10–12+ years in Data Engineering Cloud Engineering or Solution Architecture
- 5+ years hands-on Databricks Lakehouse experience
- Experience leading enterprise-scale cloud data platform implementations
- Strong client-facing experience with technical and business stakeholders
- Experience mentoring engineering teams and leading technical design discussions
- Strong hands-on experience with Unity Catalog Delta Live Tables Photon Engine and Lakehouse Federation
- Experience implementing CI/CD pipelines for data platforms
- Proficiency with Terraform and version control workflows
- Proficiency in Spark PySpark and Scala
- Experience with cloud infrastructure AWS Azure or GCP
- Hands-on experience with Docker and data-connected applications
- Experience with streaming technologies Kafka Kinesis Pub/Sub or Auto Loader
Nice to have
- Adaptive Builder
- High-Pace Operator
- Client Partner
- Ownership Mindset
Day to day
- Lead architecture design implementation and optimization of enterprise Databricks Lakehouse platforms
- Translate complex business requirements into scalable production-ready data solutions while mentoring engineering teams
- Own the full development lifecycle including technical design ETL ELT pipelines deployment monitoring and production support
Hiring process
- Initial Screening with CloudTech Innovations
- Client Introduction phone call
- Technical Deep-Dive interview with Implementation Partner
- Final interview with end client