Kyndryl is a company that designs, builds, manages, and modernizes mission-critical technology systems. They are seeking a Data Engineer who will be responsible for crafting data platforms, ensuring the availability of refined data sets, and transforming raw data into actionable insights for strategic decision-making.
Responsibilities:
- Ensuring a treasure trove of pristine, harmonized data is at everyone's fingertips
- Engineering the backbone of our data infrastructure, ensuring the availability of pristine, refined data sets
- Understanding project objectives and requirements from a business perspective and converting this knowledge into a data puzzle
- Delving into the depths of information to uncover quality issues and initial insights, setting the stage for data excellence
- Architecting data pipelines, using expertise to cleanse, normalize, and transform raw data into the final dataset
- Scrutinizing data solutions, ensuring they align with business and technical requirements
- Maintaining lifecycle management expertise to ensure data remains fresh and impactful
Requirements:
- Minimum of 5+ years of experience working as a Data Engineer and/or in cloud modernization
- Expertise in data mining, data storage and Extract-Transform-Load (ETL) processes
- Experience in data pipelines development and tooling, e.g., Glue, Databricks, Synapse, or Dataproc
- Experience with both relational and NoSQL databases, PostgreSQL, DB2, MongoDB
- Excellent problem-solving, analytical, and critical thinking skills
- Ability to manage multiple projects simultaneously, while maintaining a high level of attention to detail
- Communication Skills: Must be able to communicate with both technical and non-technical colleagues, to derive technical requirements from business needs and problems
- Degree in a scientific discipline, such as Computer Science, Software Engineering, or Information Technology
- Experience in Data Modelling, to create conceptual model of how data is connected and how it will be used in business processes
- Professional certification, e.g., Open Certified Technical Specialist with Data Engineering Specialization
- Cloud platform certification, e.g., AWS Certified Data Analytics – Specialty, Elastic Certified Engineer, Google Cloud Professional Data Engineer, or Microsoft Certified: Azure Data Engineer Associate
- Understanding of social coding and Integrated Development Environments, e.g., GitHub and Visual Studio