Working knowledge of using Python or other languages for creating pipelines and data processing
Build high-performance algorithms, predictive models, and prototypes.
Ensure that all systems meet the business/company requirements as well as industry practices.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing 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 big data technologies.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
Work with data and analytics experts to strive for greater functionality in our data systems.
Build processes supporting data transformation, data structures, metadata, dependency and workload management.
Proficient understanding of distributed computing principles
Management of Hadoop cluster, with all included services
Ability to solve any ongoing issues with operating the cluster
Proficiency with Hadoop v2 or higher, MapReduce, HDFS
Experience with building stream-processing systems, using solutions such as Storm or Spark-Streaming
Good knowledge of Big Data querying tools, such as Pig, Hive, and Impala
Experience with Spark
Experience with integration of data from multiple data sources
Experience with NoSQL databases, such as HBase, Cassandra, MongoDB
Knowledge of various ETL techniques and frameworks, such as Flume