Key responsibilities
Develop the vision of data quality as a process of continuous and evolutionary improvement, which should help meet current and future sustainability needs in decision-making and automation (data driven).
Design, test, develop and document data quality processes and their consequent results.
The main tasks associated with this role are to use data quality tools, to validate and analyze the main sources of information, and to broadly support the quality of these sources. Search for duplicate, redundant, or out-of-context records.
Generate synergies with the teams that guard the data to generate summaries and automate them in order to validate data quality.
Analyse and translate customer needs into quality requirements on enterprise data models.
Investigate the right technologies to solve data quality problems over the course of projects.
Guide team members, through in-house consulting, transmission of best practices in project development.
Manage internal customer expectations and adapt to changes in business, operations and technology.
Skills
Knowledge of SQL language.
Knowledge in data analysis methodologies.
Knowledge of Data Modelling theory
Knowledge in public cloud technologies, especially The Google Cloud Platform.
Knowledge of data governance frameworks and data quality theory.
Knowledge of system architecture and the interaction between different technical data management components (such as DWH, ODS, among others) is desirable but not exclusive.
Algorithms, Statistics, Data Science, Python, Model Deployment in GCP Cloud. GCP Cloud AI Platform, TensorFlow. Looking for Data Scientist in E-Commerce domain to implement variety of data science use cases in different areas of e-commerce site and operations. Should have good mix of statistics, algorithm and technical knowledge to develop and deploy end to end AI/ML models in GCP cloud.