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|Company Name||Global Consulting Firm|
|Location||New York, Pittsburgh, Dallas, United States|
|Date Posted||June 13, 2018|
As a data engineer, you will collaborate with colleagues on national and international client projects. Together with your clients, you will develop superior IT concepts and digital solutions as well as execute technical implementations actively and on site, applying your sound technical know-how, your understanding of business contexts, and your analytical and conceptual skills.
- Design and implement data architectures in production environments
- Implementation of data orchestration pipelines, data sourcing, cleansing, augmentation and quality control processes
- Deployment of machine learning models in production
- Translation of business needs into data architecture solutions
- Contribution to overall solution, integration and enterprise architectures
- Development of data landscape modernization architectures and roadmaps
- Deep understanding of relational and warehousing database technology working with at least one of the major databases platforms (Oracle, SQLServer, Teradata, MySQL, or Postgres)
- Practical experience with big data processing frameworks and techniques such as HDFS, Map/Reduce, Storage formats (Avro, Parquet), Stream processing, etc.
- Strong working knowledge of data processing tools using SQL, Spark, Python or similar open source and commercial technologies
- Knowledge and familiarity with machine learning models application and production pipelines
- Solid foundation in solution architectures and integration architectures
- 4+ years of large scale, full life cycle data implementation projects
- Must be able to travel up to 80% to client sites as an engineering expert, when required
- Experience setting up and managing cloud (AWS, Azure) and on-premise infrastructures
- Knowledge of Java/Scala especially in relation to big data open source software
- Experience with Cloudera, Hortonworks or MapR
- Knowledge of non-relational (Cassandra, MongoDB) databases.
- Predictive analytics and machine learning experience (scikit-learn, Tensorflow, MLlib, recommendation systems)
- Experience with integrating to back-end/legacy environments
- Experience with industries such as FIs, INS, High Tech and Retail/CPG