Data Engineer - Databricks @ Boston, MA - onsite 4 days (LOCAL CANDIDATES ONLY!)

Overview

On Site
$50 - $50
Contract - W2

Skills

Databricks
ETL
SQL
Scala
Spark
Data frames
Notebooks
Pyspark
Azure

Job Details

Job Title: Data Engineer - Databricks

Location: Boston, MA - onsite 4 days (LOCAL CANDIDATES ONLY!)

Duration: 6 months

Rate: $50/hr

Mode of interview: In-person interview

Digital : Microsoft Azure~Digital : Scala~Digital : Databricks~Digital : PySpark~PL/SQL

 

Data Engineer - Databricks

- 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.

- Strong critical thinking, communication, and problem-solving skills is essential.

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