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IBM Entry Level - Data Engineer United States, New York, Buffalo 120600194
16.12.2024
As an entry level 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
• Ability to incorporate a variety of statistical and machine learning techniques
• Basic understanding of Cloud (AWS,Azure, etc)
• 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
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
• Ability to incorporate a variety of statistical and machine learning techniques
• Basic understanding of Cloud (AWS,Azure, etc)
• 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
- US Citizenship required. Candidates must be able to get Federal clearance for client work.
- Candidates must be local to or able to relocate to Buffalo, NY, and able to work onsite 3 days a week.
Preferred Technical and Professional Expertise
• Basic understanding or experience with predictive/prescriptive modeling skills
• 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 ask business and industry questions to identify appropriate modeling techniques
• Ability to communicate results to technical and non-technical audiences
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