Data Engineer-Data Platforms
About the role
Introduction
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
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 Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs.
Your primary responsibilities include:
- Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements.
- Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization.
- Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too
Required education
Bachelor's Degree
Preferred education
Master's Degree
Required technical and professional expertise
- Strong proficiency in Python: Expertise in Python programming with a focus on data processing and manipulation.
- 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.
- SQL Proficiency: Experience writing optimized SQL queries for large-scale data analysis and transformation.
- Data Processing Frameworks: Knowledge of data processing libraries such as Pandas, NumPy, and Dask.
- Cloud Platforms: Experience working with cloud platforms like AWS, Azure, or GCP, including using cloud storage systems
Preferred technical and professional experience
- Understanding of Devops.
- Experience in building scalable end-to-end data ingestion and processing solutions
- Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala
ABOUT BUSINESS UNIT
Not included in the source posting: qualifications, benefits.
Skills
Who can apply
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