Middle Big Data Engineer, Communication Services

Job description

    Buenos Aires
We help you grow in your profession


Our client is a global provider of testing, analytics, and security solutions for the telecommunications sector.
We invite you to our company, not a project


DataArt’s specialists are helping to develop an analytical solution which tracks transactions that determine the quality of customer experience with network service providers (QoE). From these transactions, key indicators are displayed, such as radio frequency performance, base signal speed, and service performance (VoLTE, SMS). All metrics are combined into the final QoE estimates, which are used to determine hot spots and help localize and solve service quality problems.
We create a restriction-free environment
We let you concentrate on your job


  • Drive and be accountable for solution designs and discovery exercises for both new and existing clients
  • Elicit business needs and requirements, determine the project's scope, team, and timeline
  • Lead project implementation from ideation to completion
  • Serve as a top-level escalation point for technical and process concerns, which may arrive from either the implementation team or client (or both)
  • Mentor everyone on your team (including developers, QAs, BAs, PMs, DevOps, business stakeholders, and yourself)
  • Read, listen, and learn a lot


  • Solid experience as an Architect/Tech lead with 5 years in commercial projects
  • Proficiency in one of the following programming languages: Java, Scala, or Python
  • Hands-on experience with Hadoop, NoSQL, MPP technologies, processing frameworks, or other Big Data technology areas: data ingestion, consolidation, streaming, or batching
  • Experience in at least one of the processing and computation frameworks: Kafka Streams, Storm, Spark, Flink, Beam/DataFlow, Akka, etc.
  • Expertise in at least one of the RDBMS or NoSQL engines: PostgreSQL, MySQL, Cassandra, HBase, Elasticsearch, Redis, MongoDB, Impala, Kudu, etc.
  • Practice implementing Data Lakes, Data Warehousing or analytics systems as a big plus point
  • Cloud practice with AWS, GCP, or Azure
  • Spoken English

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