Senior Data Engineer

Job Description

Are you passionate about bringing systems to life Do you have the drive to innovate Do you want to help develop a new high-profile on-line trading application Take pride in the quality of software delivered for each development iteration We re looking for someone like that to join us and: be a part of a high-performing team on a high-profile project. mine and analyze data from various sources to provide actionable insights deliver actionable insights to stakeholders through rich visualizations and presentations interpret, explain, and communicate complex models, analysis, and recommendations in a clear and precise manner discover and locate data, collect and clean data, design, build, validate and deploy statistical and machine learning models to address complex and strategic challenges leverage data and insights to identify risks, reduce false positives, minimize exceptions and manual interventions, and optimize processes and way of working operationalize in-house developed solutions in collaboration with various business and technical/IT stakeholdersYour teamIs enabling other development teams to provide their solutions inside integrated platform. It s a leading project that is designed as microservice ecosystem with state-of-the-art technologies composed into one multifunctional portal. You will be joining the Neo Personalization team within UBS Investment Bank to develop high performance streaming applications and use cutting edge machine learning technologies. You will work closely with Architect, Developers using the Platform, Quality Assurance and Security professionals., strong knowledge of and experience with statistics experience with building stream-processing systems, using solutions such as Storm or Spark-Streaming programming experience, ideally in Python, Spark, Kafka or Java, and a willingness to learn new programming languages to meet goals and objectives. in-depth knowledge of Hadoop, Spark, and similar frameworks. strong working knowledge of Python and solid understanding of SQL for data wrangling, data analysis and modelling experience with Big Data ML toolkits, such as Mahout, SparkML, or H2O experience processing large amounts of structured and unstructured data, including integrating data from multiple sources. experience of NoSQL and RDBMS databases including Redis and MongoDB/Cassandra/Cosmos broad understanding and hands-on experience in developing digital solutions by applying machine learning and deep learning models for classification, clustering, anomaly detection, text recognition and natural language processing (NLP) etc. familiarity with machine learning model development workflow, good understanding of data exploration, data processing and feature engineering techniques, and experience to develop and deploy machine learning solutions end-to-end basic knowledge of ML Ops (model lifecycle, setting up environments, using pipelines etc.) usage of code versioning control systems and project tracking tools (e.g., GitLab, JIRA etc.) knowledge of predictive analytics techniques such as regression, factor analysis, time series, reinforcement learning etc. is a plus experience with Big Data tools (e.g., Hadoop, Spark, Kafka etc.) expertise in visualization tools (e.g., Tableau) experience with Cloud Computing (AWS, Azure) and containerisation tools (Docker, Kubernetes) experience with data streaming and storage technology (Kafka, ELK stack) fluency with UNIX command line tools. knowledge of agile development practices (Scrum, XP, Kanban etc) experience with project and issue tracking tools (JIRA, etc.) You are: focused on quality an excellent communicator aware of on-going technology trends and know pragmatically leverage their benefits quick learner comfortable working independently, as well as in a team-oriented, collaborative environment fluent in English*#LI-SS1

Keyskills :
content managementemailsqlanalyticsapachenatural language processingbig datatime seriesdata analysisdeep learningdata streamingdata wranglingcloud computingdata processing