Job Title: Databricks Engineer (Scala Spark) Location: Boston, MA (Hybrid Onsite) Type: W2 (Locals Preferred) Roles & Responsibilities - Recognize the current application infrastructure and suggest new concepts to improve performance
- Document the best practices and strategies associated with application deployment and infrastructure support
- Produce reusable, efficient, and scalable programs, and also cost-effective migration strategies
- Develop Data Engineering and ML pipelines in Databricks and different AWS services, including S3, EC2, API, RDS, Kinesis/Kafka and Lambda to build serverless applications
- Work jointly with the IT team and other departments to migrate data engineering and ML applications to Databricks/AWS
- Comfortable to work on tight timelines, when required.
Skill Sets Required - Good decision-making and problem solving skills
- Solid understanding of Databricks fundamentals/architecture and have hands on experience in setting up Databricks cluster, working in Databricks modules (Data Engineering, ML and SQL warehouse).
- Knowledge on medallion architecture, DLT and unity catalog within Databricks.
- Experience in migrating data from on-prem Hadoop to Databricks/AWS
- Understanding of core AWS services, uses, and AWS architecture best practices
- Hands-on experience in different domains, like database architecture, business intelligence, machine learning, advanced analytics, big data, etc.
- Solid knowledge on Airflow
- Solid knowledge on CI/CD pipeline in AWS technologies
- Application migration of RDBMS, java/python applications, model code, elastic etc.
- Solid programming background on scala, python
- Experience with Docker and Kubernetes is a plus
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