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Data Engineer-Data Platforms

Data Engineer-Data Platforms

IBM

0 years

0 Lacs

Pune Maharashtra India

Posted:2 days ago| Platform:

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Skills Required

data consulting collaboration ai technology portfolio development design support coding testing agile apache spark pyspark architecture hadoop kafka engineering etl python programming processing sql writing analysis aws azure gcp storage drive strategy rest network

Work Mode

On-site

Job Type

Full Time

Job Description

Introduction

A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe. You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio

Your Role And Responsibilities

As a Data Engineer at IBM, you'll play a vital role in the development, design of application, provide regular support/guidance to project teams on complex coding, issue resolution and execution.

Your primary responsibilities include:
Lead the design and construction of new solutions using the latest technologies, always looking to add business value and meet user requirements.
Strive for continuous improvements by testing the build solution and working under an agile framework.
Discover and implement the latest technologies trends to maximize and build creative solutions

Preferred Education

Master's Degree

Required Technical And Professional Expertise

Experience with Apache Spark (PySpark): In-depth knowledge of Spark’s architecture, core APIs, and PySpark for distributed data processing.
Big Data Technologies: Familiarity with Hadoop, HDFS, Kafka, and other big data tools. Data Engineering Skills: Strong understanding of ETL pipelines, data modeling, and data warehousing concepts.
Strong proficiency in Python: Expertise in Python programming with a focus on data processing and manipulation. Data Processing Frameworks: Knowledge of data processing libraries such as Pandas, NumPy.
SQL Proficiency: Experience writing optimized SQL queries for large-scale data analysis and transformation.
Cloud Platforms: Experience working with cloud platforms like AWS, Azure, or GCP, including using cloud storage systems

Preferred Technical And Professional Experience

Define, drive, and implement an architecture strategy and standards for end-to-end monitoring.
Partner with the rest of the technology teams including application development, enterprise architecture, testing services, network engineering,
Good to have detection and prevention tools for Company products and Platform and customer-facing

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Data Engineer-Data Platforms