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Group Cloud Data Engineer

Hyderabad, TG, IN, 500081

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About our company

Fortuna has become an established brand among customers within just a few years. We became a proud international Family of companies carrying Fortuna Entertainment Group from the first betting shop.

We want to go further and be known for having the best tech department offering our employees the usage of modern technologies, and being part of many exciting projects. Our new home is the remarkable Churchill II building which has a view of Prague.

Every detail underlines the company's corporate culture and represents our values. The workplace layout is 100% ecological, providing ideal conditions for everyday work. We all work as one team and treat each other with respect, openness, a sense of honor and respect for individual and cultural differences.

POSITION TITLE: Group Cloud Data Engineer

 

Key Purpose Statement – Core mission

The core purpose of a Cloud Data Engineer will be to manage and oversee data management on the cloud datalake platform. The successful candidate will be responsible for the data storage, data processing and data optimization, and monitoring of all Azure data resources with a specific focus on Datalake. The role requires expert-level knowledge and proven experience in handling large-scale data environments, ensuring high performance and efficiency.

 

RESPONSIBILITIES

Design and Development:

  •    Design, develop, and maintain scalable data lake solutions using Microsoft Fabric, Databricks, and Azure Data Lake Storage (ADLS)
  •    Develop and maintain ETL processes to integrate data from various sources into the data lake.
  •    Ensure data is organized and accessible for data scientists, analysts, and other stakeholders.

Synapse Management:

  •    Maintain Synapse SQL pools and serverless, ensuring optimal performance and reliability.
  •    Implement and manage data security policies, data backup, and data restore procedures.
  •    Monitor and troubleshoot query performance issues, executing performance tuning as needed.
  •    Develop and implement strategies for data partitioning and indexing to improve query performance.

Cloud Data Platform Management:

  •   Optimize Azure data lake storages
  •   Utilize cloud-native tools and services to enhance data processing and storage capabilities.
  •   Ensure high availability and fault tolerance for critical data systems.
  •   Implement and manage CI/CD pipelines for data engineering projects.

Maintenance and Optimization:

  •    Monitor and optimize the performance of data solutions, ensuring high availability and scalability.
  •    Implement best practices for data management, including data lifecycle management, data governance, and data security.

Documentation and Training:

  •    Document data lake architecture, data flows, and processes.
  •    Provide training and support to team members and stakeholders on using the data lake.

 

REQUIREMENTS - KNOWLEDGE, SKILLS AND EXPERIENCE

Education

  • Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field.
  • Minimum of 5 years of experience in cloud data architecture and solution design, with at least 3 years specializing in Azure
  • At least 3 years of hands-on experience with  Azure Synapse , DevOps practices, and cloud data platforms.
  • Proven track record of successfully designing and deploying large-scale, complex cloud data solutions.
  • Over  2 years of experience in azure sql on pool and serverless administration would be preferrable.

Qualifications, Technical Skills

  • Deep understanding of Azure data services, including compute, storage,  databases, and security.
  • Deep expertise in Synapse SQL, including architecture, security, performance tuning, and troubleshooting.
  • Extensive experience with cloud platforms (AWS, Azure, GCP) and their data services.
     - In-depth knowledge of DevOps tools and practices, including CI/CD, automation.
    - Advanced SQL skills and familiarity with database technologies (e.g., MySQL, PostgreSQL, NoSQL).
  • Strong understanding of data integration, ETL processes, and data warehousing.

Work and personality characteristics required:

  • Excellent problem-solving and analytical skills.
  • Strong communication and leadership abilities.
  • Ability to work independently and lead collaborative projects.

 

 

 

 

 

 

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