Overview
On Site
$50 - $50
Contract - W2
Skills
Databricks
ETL
ELT
SQL
Data pipelines
Data Frames
Scala
Spark
Notebooks
Pyspark
Azure cloud
Job Details
Job Title: Data Engineer Databricks
Location: Boston, MA - onsite 4 days (LOCAL CANDIDATES ONLY!)
Duration: 6 months
Rate: $50/hr
Digital : Microsoft Azure~Digital : Scala~Digital : Databricks~Digital : PySpark~PL/SQL
- Must have at least 8+ years of extensive Data Engineering Experience in Databricks, ETL/ELT using Data pipelines, SQL/Procedure experience.
- Must have 8+ Years of hands-on development proficiency in implementing Databricks solutions using Scala and Spark with Data frames and Notebooks/SQL.
- Must have 8+ Years of hands-on development and performance tuning/enhancement experience in Scala/PySpark and SQL.
- Must have 8+ Years of hands-on development experience in working on Azure Cloud.
- Must have strong experience with Databricks, including developing and optimizing Spark jobs, data transformations, and data processing workflows.
- Must have experience and a good understanding on the below topics
- Databricks Delta Lake storage
- Unity Catalog
- Autoloader
- Lakehouse Architecture
- Medallion Architecture
- Databricks Serverless Options.
- Dataset and Data frame
- Databricks Clusters Configuration and Sizing
- Databricks Job Orchestration
- Spark Structured Streaming
- Must have experience with complex and large volume data streaming and data transformations using Azure Databricks.
- Must have extensive experience in Datawarehouse/Data Lakehouse implementations.
- Must have experience with monitoring, debugging, and resolving issues in live Databricks jobs.
- Must have strong hands-on expertise in troubleshooting DevOps pipelines, Azure, and AKS services
- The candidate should be able to provide Data Ingestion, Streaming and Transformations solutions and do development work.
- Experience in Apache Big Data implementations with programming proficiency like PySpark, R or Java prior to Databricks is advantageous.
- Good to have experience with containerization technologies such as Docker and Kubernetes.
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