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; including Software and Red Hat.
Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in ground breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.
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.
We are looking for a highly motivated Data Engineer to join our team and work on the development of robust data solutions, from modeling to the implementation of pipelines and ETL processes in modern, high-scale environments.
Responsibilities
- Develop, optimize and maintain data pipelines and ETL processes using Python and SQL.
- Working in development environments such as JupyterLab or Visual Studio Code, with code versioning via Gitlab.
- Modeling and architecting relational databases (DB2, Oracle, MySQL) and participating in the definition of data storage and retrieval strategies.
- Designing and implementing Big Data solutions using Hadoop, HDFS, Hive, Spark and Hue (desirable).
- Apply good programming practices and unit testing techniques to ensure data integrity and quality.
- Document processes, data flows and solution architecture to facilitate maintenance and team understanding.
- Collaborate with multidisciplinary teams to understand business requirements and transform demands into scalable solutions.
- Ensuring compliance with the General Data Protection Act (GDPR) at all stages of the data lifecycle (basic knowledge desirable).
- Proven experience in Python and SQL for data manipulation and transformation.
- Experience with relational databases (DB2, Oracle; MySQL desirable).
- Knowledge of data architecture and modeling.
- Experience in ETL processes and strategies, preferably using Datastage or NiFi (desirable).
- Familiarity with Big Data tools and frameworks: Hadoop, HDFS, Hive, Spark, Hue (desirable).
- Experience with JupyterLab or Visual Studio Code development environments and version control with Gitlab.
- Basic knowledge of the GDPR is a plus.
- Ability to work in a team, good communication skills and a collaborative profile.
- Certifications in Big Data, Data Engineering or cloud platforms.
- Experience with pipeline automation and continuous integration.
- Experience in agile environments and highly scalable projects.