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.
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.
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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.
Your Role and Responsibilities
As a Data Engineer at IBM you will harness the power of data to unveil captivating stories and intricate patterns. You'll contribute to data gathering, storage, and both batch and real-time processing.
Collaborating closely with diverse teams, you'll play an important role in deciding the most suitable data management systems and identifying the crucial data required for insightful analysis. As a Data Engineer, you'll tackle obstacles related to database integration and untangle complex, unstructured data sets.
In this role, your responsibilities may include:
- Implementing and validating predictive models as well as creating and maintain statistical models with a focus on big data, incorporating a variety of statistical and machine learning techniques
- Designing and implementing various enterprise seach applications such as Elasticsearch and Splunk for client requirements
- Work in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviors.
- Build teams or writing programs to cleanse and integrate data in an efficient and reusable manner, developing predictive or prescriptive models, and evaluating modeling results
Required Technical and Professional Expertise
- 2 to 5 years of full-time working experience in Data Engineering domain.
- Expertise in Python, SQL, Spark, and Kafka and must have excellent understanding of databases.
- Must have experience with on-premise data integration on-premise data integration.
- Expertise in Data Modeling, industrial modeling, Analytic model, data architecture, dimensional modeling, 3rd normal form model, kimball model, Inmon model, Data Integration, Business Intelligence.
- Demonstrated ability in solutioning covering data ingestion, data cleansing, ETL, data mart creation and exposing data for consumers.
Preferred Technical and Professional Expertise
Cloud Data Engineer Certification.