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Manager Data Engineer
Houston, Texas
Contract Position
It appears that you have already applied to this job.
Applied on April 16, 2021
Job Id #46151 Posted March 9, 2021


 Remote

Lookin for a Data Engineer to pull data from logistics system, supply systems, Salesforce, SAP, etc. Pulling data from sources into Data Lake. Building Data Lake on AWS. Candidates should have worked in a Data ecosystem and be familiar with AWS. AWS ecosystem and services is the basic requirement. Agile Scrum.  

Manager

Basic Qualifications: • A minimum of three years developing and deploying large scale advanced analytics applications into a production environment • Minimum of five years, hands-on experience collaboratively developing code in object-oriented language for a production environment, including: • Experience working in Linux environment (bash scripting) • SQL (Data Normalization) • Python • Data Structures (arrays, lists, stacks, queues, trees, dictionaries, etc.) • Experience in data mining techniques and methodologies (data prep/modeling, classification, regression, clustering, causal modeling, AI, machine learning, ensemble approaches) • Advanced experience in data visualization tools with a strong grasp of effective data modeling and visualization practices • Experience rapidly developing proof of concepts and testing new ideas, as well as scale these ideas into production ready models • Experience leveraging cloud platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP) or Microsoft Azure Preferred Qualifications: • Advanced, relevant education, advanced Degree (Masters or PhD) in engineering, mathematics, physics, economics, computer science, statistics, or business analytics • Experience with AWS big data services (Kinesis, Glue, EMR, Spectrum etc.) • Experience with ETL & analytics tools (AWS, Matillion, Tallend, AtScale, etc.) • Experience with data virtualization technologies (Denodo, etc.) • Experience with data visualization tools (PowerBI, Tableau, etc.) • Experience with Scrum/Agile delivery processes and DevOps concepts (i.e. CI/CD) • Experience with data storage technologies (Redshift, S3, Hadoop, Graph, etc.) • Experience with cloud Platforms (AWS, Azure, Google) • Experience with multiple languages and syntax (Python, SQL, Apache Spark, etc.) • Experience with Container based orchestration of big data pipelines • Rest APIs for pulling or pushing data to from / to internal and external applications, Comments: Amit Singh is the primary point of contact for this role. Basic Qualifications: • A minimum of three years developing and deploying large scale advanced analytics applications into a production environment • Minimum of five years, hands-on experience collaboratively developing code in object-oriented language for a production environment, including: • Experience working in Linux environment (bash scripting) • SQL (Data Normalization) • Python • Data Structures (arrays, lists, stacks, queues, trees, dictionaries, etc.) • Experience in data mining techniques and methodologies (data prep/modeling, classification, regression, clustering, causal modeling, AI, machine learning, ensemble approaches) • Advanced experience in data visualization tools with a strong grasp of effective data modeling and visualization practices • Experience rapidly developing proof of concepts and testing new ideas, as well as scale these ideas into production ready models • Experience leveraging cloud platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP) or Microsoft Azure Preferred Qualifications: • Advanced, relevant education, advanced Degree (Masters or PhD) in engineering, mathematics, physics, economics, computer science, statistics, or business analytics • Experience with AWS big data services (Kinesis, Glue, EMR, Spectrum etc.) • Experience with ETL & analytics tools (AWS, Matillion, Tallend, AtScale, etc.) • Experience with data virtualization technologies (Denodo, etc.) • Experience with data visualization tools (PowerBI, Tableau, etc.) • Experience with Scrum/Agile delivery processes and DevOps concepts (i.e. CI/CD) • Experience with data storage technologies (Redshift, S3, Hadoop, Graph, etc.) • Experience with cloud Platforms (AWS, Azure, Google) • Experience with multiple languages and syntax (Python, SQL, Apache Spark, etc.) • Experience with Container based orchestration of big data pipelines

 

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