Role Overview:
- 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.
Responsibilities (in this role your responsibilities may include):
- Implementing and validating predictive models as well as creating and maintaining statistical models with a focus on big data, incorporating a variety of statistical and machine learning techniques.
- Designing and implementing various enterprise search applications such as Elasticsearch and Splunk for client requirements.
- Working 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 behaviours.
Required Education:
Required Technical and Professional Expertise:
- Good hands-on experience in DBT is required.
- ETL DataStage and Snowflake - preferred.
- Ability to use programming languages like Java, Python, Scala, etc., to build pipelines to extract and transform data from a repository to a data consumer.
- Ability to use Extract, Transform, and Load (ETL) tools and/or data integration, or federation tools to prepare and transform data as needed.
- Ability to use leading edge tools such as Linux, SQL, Python, Spark, Hadoop and Java.
Preferred Technical and Professional Experience:
- You thrive on teamwork and have excellent verbal and written communication skills.
- Ability to communicate with internal and external clients to understand and define business needs, providing analytical solutions.
- Ability to communicate results to technical and non-technical audiences.
