Dun & Bradstreet

Why We Work at Dun & Bradstreet

Dun & Bradstreet unlocks the power of data through analytics, creating a better tomorrow. Each day, we are finding new ways to strengthen our award-winning culture and accelerate creativity, innovation and growth. Our 6,000+ global team members are passionate about what we do. We are dedicated to helping clients turn uncertainty into confidence, risk into opportunity and potential into prosperity. Bold and diverse thinkers are always welcome. Come join us! Learn more at dnb.com/careers.

Key Responsibilities:

• Design and Develop Data Pipelines: Architect, build, and deploy scalable and efficient data pipelines within our Big Data ecosystem using Apache Spark and Apache Airflow. Document new and existing pipelines and datasets to ensure clarity and maintainability.
• Data Architecture and Management: Demonstrate familiarity with data pipelines, data lakes, and modern data warehousing practices, including virtual data warehouses and push-down analytics. Design and implement distributed data processing solutions using technologies like Apache Spark and Hadoop.
• Programming and Scripting: Exhibit expert-level programming skills in Python, with the ability to write clean, efficient, and maintainable code.
• Cloud Infrastructure: Utilize cloud-based infrastructures (AWS/GCP) and their various services, including compute resources, databases, and data warehouses. Manage and optimize cloud-based data infrastructure, ensuring efficient data storage and retrieval.
• Workflow Orchestration: Develop and manage workflows using Apache Airflow for scheduling and orchestrating data processing jobs. Create and maintain Apache Airflow DAGs for workflow orchestration.
• Big Data Architecture: Possess strong knowledge of Big Data architecture, including cluster installation, configuration, monitoring, security, resource management, maintenance, and performance tuning.
• Innovation and Optimization: Create detailed designs and proof-of-concepts (POCs) to enable new workloads and technical capabilities on the platform.
• Collaborate with platform and infrastructure engineers to implement these capabilities in production.

Key Requirements:

• Minimum of 10 years hands-on experience with Big Data technologies e.g. Hadoop, Spark, Hive.
• Minimum 3+ years of experience on Spark.
• Hands on experience with Datapro is a HUGE plus.
• Minimum 6 years of experience in Cloud environments, preferably GCP.
• Any experience with NoSQL and Graph databases.
• Hands on experience with managing solutions deployed in the Cloud, preferably on AWS.
• Experience working in a Global company, working in a DevOps model is a plus.

All Dun & Bradstreet job postings can be found at https://www.dnb.com/about-us/careers-and-people/joblistings.html and https://jobs.lever.co/dnb. Official communication from Dun & Bradstreet will come from an email address ending in @dnb.com.

Notice to Applicants: Please be advised that this job posting page is hosted and powered by Lever. Your use of this page is subject to Lever's Privacy Notice and Cookie Policy, which governs the processing of visitor data on this platform.