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Lead Data Engineer
Location : Illinois, Chicago
Refer job # APQL338080

Job Responsibilities and Requirements: Position Summary: This role will lead key analytics engineering initiatives, including end to end ownership for designing and deploying Big Data products. The ideal candidate will have 10 years of technical experience and 1 to 3 years of experience with Hadoop ecosystem is a plus. This position is high visibility will need to communicate advanced technical concepts to a broad audience including very senior levels. Will also need to mentor and give direction to a team of engineers. Fundamental Components: Designs and develops complex and large scale data structures and pipelines to organize, collect and standardize data to generate insights and addresses reporting needs. Uses advanced programming skills in Python, Java or any of the major languages to build robust data pipelines and dynamic systems. Writes complex ETL (Extract / Transform / Load) processes, designs database systems and develops tools for real-time and offline analytic processing. Develop frameworks, standards & reference material for architecture and associated products. Designs data marts and data models to support Data Science and other internal customers. Acts as a mentor to junior team members to provide technical advice. Applies Aetna systems and products to consult and advise on additional efforts across multiple domains spanning broader enterprise. Collaborates with data science team to transform data and integrate algorithms and models into highly available, production systems. Uses in-depth knowledge on Hadoop architecture, HDFS commands and experience designing & optimizing queries to build scalable, modular, and efficient data pipelines. Integrates data from a variety of sources, assuring that they adhere to data quality and accessibility standards. Experiments with available tools and advises on new tools in order to determine optimal solution given the requirements dictated by the model/use case. BACKGROUND/EXPERIENCE desired: 7-10 or more years of progressively complex related experience in data science engineering. In-depth knowledge of large scale search applications and building high volume data pipelines. In-depth knowledge on Hadoop architecture, HDFS commands and experience designing & optimizing queries to build scalable, modular, and efficient data pipelines. Advanced programming skills in Python, Java or any of the major languages to build robust data pipelines and dynamic systems. Strong leadership and mentoring skills. In-depth knowledge of Healthcare is required Uses In-depth knowledge of cloud architecture to design and implement native cloud applications leveraging services such as: lambda, kinesis, SQS, S3 EDUCATION The highest level of education desired for candidates in this position is a Master's degree.



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