Job description

Job Description


  • Create and maintain optimal Data lake setup.
  • Assemble large and complex data sets that meet functional / non-functional business requirements.
  • 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 data from various sources using SQL.
  • Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL), and working familiarity with various databases.
  • Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
  • Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
  • Build processes supporting data transformation, data structures, metadata, dependency and workload management.
  • Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
  • Strong project management and organizational skills.
  • Experience supporting and working with cross-functional teams in a dynamic environment.


Requirements


  • Experience with Data Analytics services like EMR, Glue, Athena, Kinesis, MSK, Elasticsearch, Quicksight and Redshift.
  • Experience with big data tools: Hadoop, Spark, Kafka, Hive etc.
  • Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
  • Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
  • Experience with stream-processing systems: Storm, Spark-Streaming, etc.
  • Experience with object-oriented/object function scripting languages: Python, Scala, etc


Requirements


Experience with Data Analytics services like EMR, Glue, Athena, Kinesis, MSK, Elasticsearch, Quicksight and Redshift. Experience with big data tools: Hadoop, Spark, Kafka, Hive etc. Experience with relational SQL and NoSQL databases, including Postgres and Cassandra. Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc. Experience with stream-processing systems: Storm, Spark-Streaming, etc. Experience with object-oriented/object function scripting languages: Python, Scala, etc

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