Lead Data Engineer - $70bn Healthcare Company (New York/Boston)

Intelletec has partnered in helping the Nation's Premier Health Innovators (with over 25 million insurers) in helping people on their path to better health. They are building a new health care model that is easier to use, less expensive, and puts the consumer at the center of their care!!

Locations: CT-Hartford, MA-Wellesley, NY-New York

Leads and participates in the design, built and management of large scale data structures and pipelines and efficient Extract/Load/Transform (ETL) workflows.

• Key skills: Data Pipelines, ETL (short for Extract, Transform, Load), data warehouse, data warehousing, data architecture, database
• Key tools/technologies:  Programming (Python), Data Warehousing (Hadoop, MapReduce, HIVE, PIG, Apache Spark, Kafka) and databases (SQL and NoSQL)

Fundamental Components:

• Designs and develops large scale data structures and pipelines
• Writes ETL (Extract / Transform / Load) processes, designs database systems and develops tools for real-time and offline analytic processing
• Mentor junior engineers to provide technical advice
• Collaborates with the data science team to transform data and integrate algorithms and models into automated processes.
• Experience designing & optimizing queries to build data pipelines
• Builds data marts and data models to support Data Science and other internal customers.
• Experiments with available tools and advices on new tools in order to determine the optimal solution given the requirements dictated by the model/use case.

Background Experience:

• 7+ years of progressively complex related experience
• Bachelor's degree or equivalent work experience in Computer Science or related discipline (masters/PhD preferred)
• Ability to understand complex systems and solve challenging analytical problems
• Experience with bash shell scripts, UNIX utilities & UNIX Commands.
• Knowledge in Java, Python, Hive, Cassandra, Pig, MySQL or NoSQL or similar.
• Knowledge in Hadoop architecture, HDFS commands and experience designing & optimizing queries against data
• Experience building data transformation and processing solutions.
• Has strong knowledge of large scale search applications and building high volume data pipelines.