Posted Sep 02, 2019 2 views
About Job Role:
We are searching for an accountable, multitalented Data Engineer to facilitate the operations of our Data Scientists. The Data Engineer will be responsible for employing machine learning techniques to create and sustain structures that allow for the analysis of data, while remaining familiar with dominant programming and deployment strategies in the field. During various aspects of this process, you should collaborate with coworkers to ensure that your approach meets the needs of each project.
Responsibilities:
- Liaising with coworkers and clients to elucidate the requirements for each task.
- Conceptualizing and generating infrastructure that allows big data to be accessed and analyzed.
- Reformulating existing frameworks to optimize their functioning.
- Testing such structures to ensure that they are fit for use.
- Preparing raw data for manipulation by Data Scientists.
- Detecting and correcting errors in your work.
- Ensuring that your work remains backed up and readily accessible to relevant coworkers.
- Remaining up-to-date with industry standards and technological advancements that will improve the quality of your outputs.
Requirements:
- Proven experience of 3 years as a Data Engineer
- Bachelor's degree in Data Engineering, Big Data Analytics, Computer Engineering, or a related field
- Expert proficiency in Python, Java, Scala, or any two.
- Proficient understanding of distributed computing principles
- Proficiency with Hadoop, MapReduce, HDFS
- Experience with building stream-processing systems, using solutions such as Storm or Spark-Streaming.
- Management of Hadoop cluster, with all included services and ability to solve any ongoing issues with operating the cluster
- 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, Taled etc
- Good understanding of Lambda / Kappa Architecture, along with its advantages and drawbacks.
- Experience with Cloudera
- Familiarity with Data Lakes, Data Warehouses, Denodo, Qlik
- On-Premise deployment and cloud experience will be a plus.
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