Big Data Engineer

Senior Big Data EngineerAs an experienced member of our Data Engineering Platform Group, you will be responsible for building and taking ownership over the successful design and development of data engineering projects within Client's Enterprise Data Commerce Solutions division. You will be required to apply your depth of knowledge and expertise to all aspects of the data engineering lifecycle, as well as partner continuously with your many stakeholders daily to stay focused on common goals. You'll work in a collaborative, trusting, thought-provoking environment-one that encourages diversity of thought and creative solutions that are in the best interests of our customers globally.You will lead large-scale data engineering, integration and warehousing projects, build custom integrations between cloud-based systems using APIs and write complex and efficient queries to transform raw data sources into easily accessible models by using the Data integration tool with coding across several languages such as Java, Python, and SQL. Additional responsibilities include, but are not limited to architect, build, and launch new data models that provide intuitive analytics to the team and build data expertise and own data quality for the pipelines you create.Basic qualifications for consideration include: 10+ overall industry experience, 7+ years' experience with building large scale big data applications development, a bachelor's in computer science or related field, technical leadership in developing data solutions and building frameworks, expertise in solutions for processing large volumes of data, using data processing tools and Big Data platforms, hands-on experience in cloud Data stack (preference is Azure), understanding of cluster and parallel architecture as well as high-scale or distributed RDBMS, SQL experience, hands on experience on major programming/scripting languages like Java, Java experience with OOPS concepts, multithreading, conduct code reviews and strive for improvement in software engineering quality, hands-on experience in production rollout and infrastructure configuration, demonstrable experience of successfully delivering big data projects using Kafka, Spark, exposure working on NoSQL Databases such as Cassandra, HBase, DynamoDB, and Elastic Search, experience working with PCI Data and working with data scientists is a plus, in depth knowledge of design principles and patterns, and able to tune big data solutions to improve performance.