Your responsibilities

• Develop prototypes and data-centric solutions for various users using Data Analytics (DA).
• Provide guidance, support, and training for data analytics tasks for both technical and non-technical audiences (modeling, design, architectural reviews, standards, and processes, Center of Expertise).
• Prepare architectural outputs related to data analytics (Reference Data Architecture, Data Platforms).
• Collect and analyze business requirements.
• Perform technical analyses and create specifications for data analytics solutions.
• Conduct exploratory data analyses to identify, interpret, and analyze patterns and trends in complex datasets for diagnosis and reporting purposes.
• Design, model, develop, manage, and review end-to-end data analytics products, prototypes, and proof of concepts on both on-premise and cloud data platforms, including data preparation, modeling, visualization, deployment, monitoring, and maintenance.
• Implement testing and quality assurance practices, including automated validation where relevant.
• Define and document training and support procedures.
• Maintain data analytics products, including troubleshooting, bug fixing, performance analysis, and technical migrations.
• Architect, design, deploy, and manage components of data platforms.
• Integrate and reuse COTS, SaaS and PaaS solutions.
• Design and implement data protection and security measures.
• Define testing strategies, design tests, and conduct testing.
• Establish best practices and standards.
• Conduct technology watch, evaluate technologies, and contribute to platform definition and strategy documents.

Your profile

• Bachelor’s degree in Computer Science, Information Technology, or related field.
• Strong business analysis skills.
• Strong analytical mindset with the ability to identify patterns and gaps when exploring data.
• Solid knowledge of statistical analysis and data-driven decision-making.
• Extensive experience in data analytics and data engineering practices.
• Proficiency in programming languages for data analytics (e.g., Python, R).
• Experience in developing and industrializing data analytics solutions.
• Knowledge of testing and quality assurance practices.
• Proficiency with visualization tools (e.g., Power BI).
• Strong knowledge of SQL databases (Oracle, SQL Server) and NoSQL databases (MongoDB, Neo4j).
• Experience with orchestration tools (e.g., Airflow) and ETL tools (e.g., DBT, SSIS).
• Familiarity with search engines (e.g., ElasticSearch, SOLR).
• Knowledge of data modeling for data lakes and data warehouses.
• Experience with cloud environments and containerization.
• Fluent English; any additional language is an asset.

Client’s offer

• Working alongside recognized experts.
• Excellent training and access to reputed expertise.