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Data Engineer

Latest job opening in Ericsson | Associate Engineer | Freshers job 2024

Data Engineer


Job Description

Latest job opening in Ericsson for Data Engineer. As a data engineer, you need to be adaptable, creative, and able to take constructive criticism well in order to succeed. A formidable data engineer will have exceptional interpersonal skills and an insatiable curiosity.Data engineers provide frameworks that prepare information for use by data scientists using a variety of tools and approaches. Among the most popular programming languages used by data engineers are Python, Java, R, and C++.

We are seeking a talented and dedicated Data Engineer to join our team at Ericsson. The successful candidate will be responsible for developing and delivering data solutions to fulfill our business needs and specifications. By creating and optimizing data pipelines and data models for our analytical solution’s data lake / data warehouses, you’ll be contributing to specific microservices we offer. The role also encompasses the responsibility for managing all data entering our data lake/DWH, ensuring the content, format, and integrity remain optimal throughout the data’s lifecycle.

Skills set Required for this Job :
  • a bachelor’s degree in computer science, data engineering, big data analytics, or a similar profession.
  • It is beneficial to have a master’s degree in a relevant discipline.
  • shown expertise in software development, data engineering, or a related field.
  • expert knowledge in SQL, R, Java, C++, and Python.
  • knowledge of Hadoop or an acceptable substitute.
  • outstanding ability to analyse and solve problems.
  • a talent for working independently and in groups.
  • meticulous in performing tasks.
  • Ability to effectively oversee a flow of work with little guidance.
Job Responsibilities
  • Python Development: Write clean, efficient, and maintainable Python code to support data engineering tasks, including data collection, transformation, and integration with machine learning models.
  • Data Pipeline Development: Design, develop, and maintain robust data pipelines that efficiently gather, process, and transform data from various sources into a format suitable for machine learning and data science tasks using ELK stack, Python and other leading technologies.
  • Spark Knowledge: Apply basic Spark concepts for distributed data processing when necessary, optimizing data workflows for performance and scalability.
  • ELK Integration: Utilize ElasticSearch, Logstash, and Kibana (ELK) for data management, data indexing, and real-time data visualization. Knowledge of OpenSearch and related stack would be beneficial.
  • Grafana and Kibana: Create and manage dashboards and visualizations using Grafana and Kibana to provide real-time insights into data and system performance.
  • Kubernetes Deployment: Deploy data engineering solutions and machine learning models to a Kubernetes-based environment, ensuring security, scalability, reliability, and high availability.
  • Machine Learning Model Development: Collaborate with data scientists to develop and implement machine learning models, ensuring they meet performance and accuracy requirements.
  • Model Deployment and Monitoring: Deploy machine learning models and implement monitoring solutions to track model performance, drift, and health.
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Job Type: In Office Job Timing: Full Time

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