Data Analyst III

at  NCR Corporation

Data Analyst III
About NCR VOYIX
NCR VOYIX Corporation (NYSE: VYX) is a leading global provider of digital commerce solutions for the retail, restaurant and banking industries. NCR VOYIX is headquartered in Atlanta, Georgia, with approximately 16,000 employees in 35 countries across the globe. For nearly 140 years, we have been the global leader in consumer transaction technologies, turning everyday consumer interactions into meaningful moments. Today, NCR VOYIX transforms the stores, restaurants and digital banking experiences with cloud-based, platform-led SaaS and services capabilities.
Not only are we the leader in the market segments we serve and the technology we deliver, but we create exceptional consumer experiences in partnership with the world’s leading retailers, restaurants and financial institutions. We leverage our expertise, R&D capabilities and unique platform to help navigate, simplify and run our customers’ technology systems.
Our customers are at the center of everything we do. Our mission is to enable stores, restaurants and financial institutions to exceed their goals - from customer satisfaction to revenue growth, to operational excellence, to reduced costs and profit growth. Our solutions empower our customers to succeed in today’s competitive landscape.
Our unique perspective brings innovative, industry-leading tech to all the moving parts of business across industries. NCR VOYIX has earned the trust of businesses large and small - from the best-known brands around the world to your local favorite around the corner.

QUALIFICATIONS AND SKILLS:

• Bachelor’s degree or higher in Computer Science, Engineering, or a related technical field.
• Proven experience in data analyst or related roles, with a strong understanding of data processing concepts and technologies.
• Knowledge of database systems such as SQL, NoSQL, and data warehousing solutions. Knowledge in Splunk is preferred.
• Experience deploying pipelines in cloud platforms such as AWS, or Azure. Knowledge in Google Cloud Platform is preferred.
• Familiarity with data visualisation tools such as Tableau or Power BI.
• Knowledge of programming languages such as Python, Java, or Scala.
• Experience with distributed computing frameworks such as Apache Spark, Hadoop, or Apache Flink.
• Strong problem-solving skills and attention to detail.
• Excellent communication and teamwork abilities.
• Experience with containerisation and orchestration tools such as Docker and Kubernetes.
  Offers of employment are conditional upon passage of screening criteria applicable to the job

• Data Pipeline Development: Design, build, and maintain scalable and efficient data pipelines to collect, process, and store structured and unstructured data from various sources.
• Data Integration: Integrate data from multiple sources such as databases, APIs, flat files, and streaming platforms into centralized data repositories.
• Data Modeling: Develop and optimize data models and schemas to support analytical and operational requirements. Implement data transformation and aggregation processes as needed.
• Data Quality Assurance: Implement data validation and quality assurance processes to ensure the accuracy, completeness, and consistency of data throughout its lifecycle.
• Performance Optimization: Monitor and optimize data processing and storage systems for performance, reliability, and cost-effectiveness. Identify and resolve bottlenecks and inefficiencies in data pipelines.
• Collaboration: Collaborate with cross-functional teams including data scientists, analysts, software engineers, and business stakeholders to understand data requirements and deliver solutions that meet business objectives.
• Documentation and Best Practices: Document data pipelines, systems architecture, and best practices for data engineering. Share knowledge and provide guidance to colleagues on data engineering principles and techniques.
• Continuous Improvement: Stay updated with the latest technologies, tools, and trends in data engineering and recommend improvements to existing processes and systems.