A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries helping them shape their hybrid cloud and AI journeys. With support from our strategic partners robust IBM technology and Red Hat you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting curiosity fuels success. You’ll be encouraged to challenge the norm explore new ideas and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.
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.
* 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
* 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
* 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