Senior Data Analyst

About the job
Responsibilities

Organizes and studies large amounts of data and business metrics to analyze and evaluate potential problems, hypotheses, and recommendations for better business performance.
Apply tools and techniques for data analysis and visualization.
Design and develop Data Marts as a foundation for Analytics. Manage, clean, abstract, and aggregate data alongside various analytical studies on that data. Manipulate and link different data sets.
Design and develop self-service business intelligence such as cubes and dashboards, which are summaries that present data and conclusions in the most appropriate format for users.
Collaborate with cross-functional teams to accomplish various objectives.

Qualifications

At least 5 years of experience working in data analytics area as Data Analyst or Data Scientist.
Bachelor/Master’s degree in the field of Computer Science / Machine Learning / Applied Statistics / Mathematics.
Analysis and synthesis (data analyst). Apply careful data analysis to produce clear findings. Experience analyzing data using SQL, Python/R.
Communication. Strong verbal and written communication skills to share insights with stakeholders. Able to translate technical concepts into non-technical language.
Data management. Understand data sources, data organization, and storage.
Data modelling, cleansing, and enrichment. Understand conceptual, logical, and physical data modeling. Experience working with ETL/ELT tools such as DBT, Pentaho, Airflow.
Data quality assurance, validation, and linkage. Understand basic data issues and check that the data and analysis look right. Understand the concept of data being fit for purpose. Understand the context of the data. Show that you know the right questions to ask and apply a curious and analytical mindset when approaching a problem. Perform data preparation and cleansing with guidance.
Data visualization. Work under direction to use the most appropriate medium to visualize data to tell a story relevant to the fully defined goals and able to be acted upon. Familiar or experienced in working with BI visualization tools such as Power BI, Tableau, Google Data Studio, Superset.
Logical and creative thinking. Identify problems in databases, data processes, data products, and services with an understanding of the level of a problem. Contribute to the implementation of remedies and preventative measures.
Project management. Awareness of project management techniques and applied in the environment. Ability to work with cross-functional teams of technical and non-technical members. Ability to work independently in a fast-paced, iterative development environment.
Statistical methods and data analysis. Understand the theoretical basis for applied practices. Begin to apply the theory to practical examples.