Azure Big Data Architect

Overview

On Site
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - 1 year(s)
100% Travel

Skills

Azure
Hive
Spark
Airflow
NiFi
Kafka
HBase
Data Lake

Job Details

Azure Big Data Architect

About the role:

We are looking for a Data Architect / Sr. Data to be based out of US region and should be able to move to customer location located in San diago . This role involves a combination of hands-on contribution, customer engagement and technical team management. As a Data Architect, you will

  1. Design, Architect, Deploy and maintain solutions on the MS Azure using different Cloud & Big Data Technologies.
  2. Manage the full life-cycle of a Data Lake / Big Data solutions from requirement gathering and analysis to platform selection, design of the architecture and deployment.
  3. Be responsible for implementing life science specific solutions which can scale on Cloud.
  4. Collaborate with a team of life science business domain experts, data scientists and application developers to develop BD solutions.
  5. Explore and learn new technologies for creative business problem solving and mentor a team of Data Engineers.

EXPERTISE AND QUALIFICATIONS

Required Experience, Skills & Competencies:

  1. Strong Hands-on experience in implementing Data Lake with technologies like Data Factory (ADF), ADLS, Databricks, Azure Synapse Analytics, Event Hub & Streaming Analytics, Cosmos DB and Purview.
  2. Experience of using big data technologies like Spark, Airflow, NiFi, Kafka, Hive, HBase or MongoDB, Neo4J, Elastic Search, Impala, Sqoop etc.
  3. Strong programming & debugging skills either in Python, Pyspark and Scala/Java. Experience of building REST services is good to have.
  4. Experience of supporting BI and Data Science teams in consuming the data in a secure and governed manner.
  5. Good understanding and Experience of using CI/CD with Git, Jenkins / Azure DevOps.
  6. Experience of setting up cloud-computing infrastructure solutions.
  7. Hands on Experience/Exposure to NoSQL Databases and Data Modelling in Hive.
  8. Good understanding in Data warehousing, data modelling, data integration knowledge.
  9. Strong SQL experience
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