Lead Data Engineer
Designs and develops complex and large-scale data structures and pipelines to organize, collect and standardize data to generate insights and addresses reporting needs
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. Behaves as mentor to junior team members to provide technical advice
Applies knowledge of 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
Uses advanced programming skills in Python, Java or any of the major languages to build robust data pipelines and dynamic systems
Integrates data from a variety of sources, assuring that they adhere to data quality and accessibility standards
Experiments with available tools and advice on new tools in order to determine optimal solution given the requirements dictated by the model/use case
The typical pay range for this role is:
Please keep in mind that this range represents the pay range for all positions in the job grade within which this position falls. The actual salary offer will take into account a wide range of factors, including location.
7 or more years of progressively complex related experience
Experience with bash shell scripts, UNIX utilities & UNIX Commands
Experience building and implementing data transformation and processing solutions
Advanced knowledge in Java, Python, Hive, Cassandra, Pig, MySQL or NoSQL or similar
Advanced knowledge in Hadoop architecture, HDFS commands and experience designing & optimizing queries against data in the HDFS environment
Has in-depth knowledge of large-scale search applications and building high volume data pipelines
Ability to leverage multiple tools and programming languages to analyze and manipulate large data sets from disparate data sources
Ability to understand and build complex systems and solve challenging analytical problems
Bachelor's degree or equivalent work experience in Computer Science, Engineering, Machine Learning, or related discipline.
Master’s degree or PhD preferred
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