Data Engineer Job at Kobo360

Kobo360 is a tech-enabled digital logistics platform that aggregates end-to-end haulage operations to help cargo owners, truck owners and drivers, and cargo recipients to achieve an efficient supply chain framework. Through an all-in-one robust logistics ecosystem, Kobo uses big data and technology to reduce logistics frictions, empowering rural farmers to earn more by reducing farm wastages and helping manufacturers of all sizes to find new markets

We are recruiting to fill the position below:

Job Position: Data Engineer
Job Location: Nigeria

Job Description 

• We are looking for a Data Engineer that will work on collecting, storing, processing, and analyzing huge sets of data.
• The primary focus will be on choosing optimal solutions to use for these purposes, then maintaining, implementing, and monitoring them.
• You will also be responsible for integrating them with the architecture used across the company.

Responsibilities

• Selecting and integrating any Data tools and frameworks required to provide requested capabilities
• Implementing the ETL process
• Monitoring performance and advising any necessary infrastructure changes
• Defining data retention policies

Skills and Qualifications

• Proficient understanding of distributed computing principles
• Management of Hadoop cluster, with all included services {{unless you are going to have specific Big Data DevOps roles for this}}
• Ability to solve any ongoing issues with operating the cluster {{unless you are going to have specific Big Data DevOps roles for this}}
• Proficiency with Hadoop v2, MapReduce, HDFS
• Experience with building stream-processing systems, using solutions such as Storm or Spark-Streaming {{if stream-processing is relevant for the role}}
• Good knowledge of Big Data querying tools, such as Pig, Hive, and Impala
• Experience with Spark {{if you are including or planning to include it}}
• 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
• Experience with various messaging systems, such as Kafka or RabbitMQ
• Experience with Big Data ML toolkits, such as Mahout, SparkML, or H2O {{if you are going to integrate Machine Learning in your Big Data infrastructure}}
• Good understanding of Lambda Architecture, along with its advantages and drawbacks
• Experience with Cloudera/MapR/Hortonwork

Method of Application
Interested and qualified candidates should send their CV to: careers@kobo360.com

Note: Even though no degree is listed, we certainly appreciate you may have one. But in this business, what matters is what you can do. You will certainly like to be part of this. So, apply.