Senior Data analyst

• Have analytical way of thinking • Are very good in interpersonal communications and must have good command over English language • Have passion for data analysis, problem solving and requirements elicitation • Have strong business and technical background • Are familiar with agile ways of working and willing to work in cross-border, cross-cultural, virtual teams • Are proactive, structured, detail-oriented and quality driven • Are able and passionate to develop in your role as assignments can vary over time • Are cooperative as a team player as well able to work independently

Your experience and background: • Experienced in relational databases design and querying, including optimization • Familiar with Big Data platforms (querying, optimization, loading and retrieving data) and at least some of the following technologies: Hadoop, Hive, Impala, pySpark, HQL • Experienced with JSON/AVRO data formats • Experienced with use and expansion of standardized data model like (Canonical Data Model) • Experienced in defining and forming business & technical requirements into understandable format. • Experienced with at least one of following programming languages: Python, R, Java • Utilized Jira and Bitbucket for project tracking and version control • Experienced in requirement analysis and refinement in data related areas • Able to collaborate with development teams (developers, architects, IT analysts)

Nice to have:

• Finance background and/or banking experience preferred

• Perform IT analysis, investigative data analysis, system design, and data modelling to support development teams.
• Take lead or facilitating role to drive functional and non-functional requirements and analysis work that involves multiple stakeholders, to design sustainable and value adding solutions.
• Ensure alignment and transparency of requirements by acting as a bridge between IT and business teams.
• Build a contextual understanding of business processes on one hand and functional/technical know-how of our solutions on the other.
• Build understanding of data model, its consumption by development teams, and if data fulfills business requirements in our IIS area.