Data Engineer-Data Platforms

In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology

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

Required education

Bachelor's Degree

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