![Ericsson](https://media.trabajo.org/img/noimg.jpg)
Data Engineer
3 weeks ago
Description
Join our Team
About this opportunity:
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.
Your Roles and Responsibilities (Data Engineer):
• 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.
• Data Quality and Governance: Implement data quality checks and data governance practices to ensure data accuracy, consistency, and compliance with data privacy regulations.
• MLOps (Added Advantage): Contribute to the implementation of MLOps practices, including model deployment, monitoring, and automation of machine learning workflows.
• Documentation: Maintain clear and comprehensive documentation for data engineering processes, ELK configurations, machine learning models, visualizations, and deployments.
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Job Insights
Based on previously hired candidates
Popular Skills of Previous Hires
Python (Programming Language) Java Software Development Database C++
Job titles of previous hires
Senior Data Engineer
Junior Engineer
Data Engineer
Data Science Engineer
System Engineer
Previous hires also worked at
HCL Technologies
Xoanon Analytics
Machine Learning
InterviewDesk
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What we offer you
Our culture
Built over a century of courageous decisions,
our core values of professionalism, respect,
perseverance and integrity shape everything
we do.
Learning and development
We believe in a growth mindset and that the future belongs to the learners. We offer the freedom and structure to evolve your skillsets, mindsets, and career.
Reward and recognition
We recognise that you should be paid in a fair way and be rewarded for the impact you create. We always aspire to recognize your impact
on our business success.
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