Data Engineer

Hello, Data Engineer Location : Chicago or Atlanta Duration : 6+ month Strong Healthcare exp. Local to any location Need Senior candidate Must have atleast 5 years of US exp. They want someone that is an expert with Python and able to code in more than one language. They want someone with Practical experience, great communication, plus hands-on experience in all phases of data modelling from conceptualization to database optimization. Data Engineer SQL, RDBMS, Spark, Scala, pySpark, Python, Java, Hive, Hadoop Ecosystem, AWS, HBase Data engineering services required:

• Build data products and processes alongside the core engineering and technology team
• Collaborate with senior data scientists to curate, wrangle, and prepare data for use in their advanced analytical models
• Integrate data from a variety of sources, assuring that they adhere to data quality and accessibility standards
• Modify and improve data engineering processes to handle ever larger, more complex, and more types of data sources and pipelines
• Use Hadoop architecture and HDFS commands to design and optimize data queries at scale
• Evaluate and experiment with Client data engineering tools and advises information technology leads and partners about new capabilities to determine optimal solutions for particular technical problems or designated use cases /

• 5+ years of hands-on experience in one or more modern Object-Oriented Programming languages (Java, Scala, Python) including the ability to code in more than one programming language.
• 5+ years of hands-on experience applying principles, best practices, and trade-offs of schema design to different database systems, including relational (Oracle, MSSQL, Postgres, MySQL) and NoSQL (HBase, Cassandra, MongoDB)
• 2+ years of hands-on experience implementing batch and real-time data integration frameworks and/or applications in private or public cloud environments (AWS, Azure, Google Cloud Platform, etc.) using various technologies (Hadoop, Spark, Impala, etc.), including assessing performance, debugging, and fine-tuning those systems
• Deep understanding of the latest data science and data engineering methods and processes to develop impactful and reusable patterns and abstractions from enterprise-level data assets
• 3+ years of hands-on experience in all phases of data modelling from conceptualization to database optimization
• Demonstrated ability to perform the engineering necessary to acquire, ingest, cleanse, integrate, and structure massive volumes of data from multiple sources and systems into enterprise analytics platforms
• Proven ability to design and optimize queries to build scalable, modular, efficient data pipelines
• Ability to work across structured, semi-structured, and unstructured data, extracting information and identifying linkages across disparate data sets
• Proven experience delivering production-ready data engineering solutions, including requirements definition, architecture selection, prototype development, debugging, unit-testing, deployment, support, and maintenance
• Ability to operate with a variety of data engineering tools and technologies; vendor agnostic candidates preferred