Data Engineer

Description

Duties & Responsibilities Create and maintain optimal data pipeline architecture, including implementing ELT process to import data from various existing data sources, and enrich data from external data sources
Assemble large, complex data sets that meet functional / nonfunctional business requirements
Identify, design, and implement internal process improvements automating manual processes, optimizing data delivery, redesigning infrastructure for greater scalability, etc.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS big data technologies
Assist in the construction of analytics tools that utilize the data pipeline to provide actionable insights into key business performance metrics
Work with key stakeholders, from Executives to Data Scientists, to assist with datarelated technical issues and support their data infrastructure needs
Keep our data separated and secure across national boundaries through multiple data centers and AWS regions
Create data tools for analytics and data scientist team members that assist them in building and optimizing our products into an innovative industry leader
Work with data and analytics experts to strive for greater functionality in our data systems
Select and integrate any Big Data tools and frameworks required to provide requested capabilities
Monitoring performance and advising of any necessary infrastructure changes
Experience and Skills Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases (e.g. Postgresql, MySQL, Microsoft SQL Server, IBM DB2, Oracle)
Experience with data extraction from nonstructured data sources, e.g Splunk, CRM Notes
Management of big data clusters (Hadoop, Accumulo), with all included services
Experience with one or more of Cloudera/MapR/Hortonworks
Ability to solve any ongoing issues with operating the cluster
Experience with building streamprocessing systems, using solutions such as Storm or Spark
Good knowledge of Big Data querying tools, such as Pig, Hive, and Impala
Experience with NoSQL databases, such as HBase, Cassandra, MongoDB
Knowledge of various ETL techniques and frameworks, such as Flume
Experience with various messaging systems, such as Kafka or RabbitMQ
Experience with Big Data ML toolkits, such as Mahout, SparkML, or H2O
Experience with one or more of Cloudera/MapR/Hortonworks
Experience with objectoriented/object function languages Python, Java, C++, Scala, C#, etc.
Operating system experience including Linux, MS Windows, Docker