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Data Engineer - DBT at NTT DATA

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

22 Jan, 26

Salary

0.0

Posted On

24 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineer, DBT, SQL, Distributed Computation, GIT, Python, Functional Programming, Scala, Apache Spark, Hadoop, Sqoop, Hive, Flume, Continuous Integration, Continuous Deployment, Azure DevOps, Databricks

Industry

IT Services and IT Consulting

Description

As a Data Engineer, your main responsibilities will involve: The project is a migration of a SAS code to DBT code, so it's important that the candidate has experience in this type of projects. Analyze data models and derive logical conclusions. Processes modeling. Hands on development and monitoring of the Azure cloud Platform and various associated components for data ingestion, transformation and processing. Effectively diagnose, isolate, and resolve complex problems pertaining to data infrastructure, including performance tuning and optimization. Designs and writes programs according to functional and non-functional requirements. Develops and maintains technical documentation. Follows established configuration/change control processes. Minimum Skills Required: As a Big Data Developer / Data Engineer, your skills and experience will ideally include: 2+ years of experience working as a Data Engineer Ability to write complex SQL queries A good understanding of distributed computation DBT GIT Python 1+ Experience in functional programming (preferably Scala - big plus) 1+ years of experience in Apache Spark 2.0 (big plus) Experience with Hadoop technologies (i.e. Sqoop, Hive, Flume etc.) Continuous Integration / Continuous Deployment (Azure DevOps) Experience in data exploration using notebooks (Databricks notebooks). Experience in automation of regular tasks(e.g. data refreshes) using bash and python scripting."

Responsibilities

The Data Engineer will be responsible for migrating SAS code to DBT code, analyzing data models, and developing on the Azure cloud platform. The role includes diagnosing and resolving complex data infrastructure issues and maintaining technical documentation.