Capgemini - Atlanta, GA
posted 2 months ago
As a Databrick Data Engineer at Capgemini, you will play a crucial role in shaping the future of cybersecurity solutions. This position is designed for individuals who are passionate about leveraging technology to enhance security measures for leading organizations. You will collaborate closely with Business Subject Matter Experts (SMEs) to understand the requirements for building a robust cybersecurity solution aimed at threat monitoring and analysis. Your expertise will be instrumental in designing a recommendation engine that effectively monitors the dark web and other data sources, safeguarding both the company and its clients from potential threats. In this role, you will work alongside architects and business stakeholders to define and grasp the requirements for metrics reports and alerts that align with the company's vision. You will need to possess a solid understanding of cybersecurity principles and risk management, as well as knowledge of the tactics, techniques, and procedures employed by cybercriminals operating on the dark web. Familiarity with the specific cybersecurity requirements and regulatory standards applicable to financial institutions is essential. Your responsibilities will also include cloud engineering and the construction of data preparation and analytics pipelines. You will be expected to have 8-10 years of hands-on experience in data analytics engineering, with a proven track record of building solutions that monitor, analyze, and interpret dark web data to identify potential security threats. Experience in designing, developing, and implementing end-to-end data engineering solutions using Databricks for large-scale data processing and integration projects is crucial. You will be responsible for optimizing data ingestion processes, ensuring data quality, reliability, and scalability, as well as performing data transformation tasks using Databricks and related technologies. Additionally, you will monitor and troubleshoot data pipelines, identifying and resolving performance issues and data quality problems. Implementing best practices for data governance, security, and privacy within the Databricks environment will be part of your role. Strong knowledge of SQL, Python, and PySpark is required, along with experience in DataOps and delivering CI/CD and DevOps capabilities in a data environment. A certification in Databricks Engineer Professional is a plus. Strong stakeholder management and communication skills are essential for success in this position.