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    Data Engineer - Bengaluru, India - Ericsson

    Ericsson
    Ericsson background
    Description

    Description

    Join our Team

    About this opportunity:

    We are searching for a skilled and committed Data Engineer to join our team at Ericsson. The successful candidate will focus on developing and delivering data solutions to meet our business needs and specifications. By creating and optimizing data pipelines and models for our analytical solutions' data lake / data warehouses, you'll be contributing to specific microservices we offer. The role also involves managing all data entering our data lake/DWH, ensuring optimal content, format, and integrity throughout the data's lifecycle.

    Your Roles and Responsibilities (Data Engineer):

    • Python Development: Write clean, efficient, and maintainable Python code for data engineering tasks, including data collection, transformation, and integration with machine learning models.
    • Data Pipeline Development: Design, develop, and maintain robust data pipelines for gathering, processing, and transforming 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 required, optimizing data workflows for performance and scalability.
    • ELK Integration: Utilize ElasticSearch, Logstash, and Kibana (ELK) for data management, indexing, and real-time visualization. Knowledge of OpenSearch and related stack would be advantageous.
    • Grafana and Kibana: Create and manage dashboards and visualizations with Grafana and Kibana to offer 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 meeting 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 governance practices to ensure data accuracy, consistency, and compliance with data privacy regulations.
    • MLOps (Added Advantage): Contribute to implementing MLOps practices, including model deployment, monitoring, and automating 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 past hires

    Popular Skills of Past Hires

    Deep Learning Python (Programming Language) Data Science Data Model Data Visualization Java Software Development Database

    Job titles of past hires

    Senior Data Engineer Data Engineer Data Science Engineer Junior Engineer Lead Data Engineer

    Past hires also worked at

    HCL Technologies Pinnacle Computing Solutions Cyber Security

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    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.

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