Data Engineer/ Data Visualization - Pisa - Takeda Pharmaceutical

2 giorni fa

Descrizione

About the Role: As a Data Engineer/Data Visualization & Analytics Expert, you will collaborate with a diverse Agile team to build high-quality data pipelines that create analytic solutions. You will focus on generating insights from connected data, ensuring advanced data-driven decision-making capabilities.

Main Responsibilities:

Data Engineering: Design, develop, optimize, and maintain data architecture and pipelines that follow ETL principles and business goals.
Data Visualization: Support Data Scientists in data sourcing and preparation to visualize data and synthesize insights of commercial value.
SQL and Python: Perform data manipulation and queries using SQL independently and develop scripts and applications in Python for complex data processing needs.
Emerging Tools: Lead the evaluation, implementation, and deployment of emerging tools and processes for analytic data engineering to improve productivity.
Technical Architectures: Partner with business analysts and solutions architects to develop technical architectures for strategic enterprise projects and initiatives.
Statistical Data Quality: Implement statistical data quality procedures on new data sources by applying rigorous iterative data analytics.
Training and Mentoring: Advise, consult, and coach other data and analytic professionals on data standards and practices.
Data Visualizations and Dashboards: Create advanced data visualizations and dashboards in Tableau or PowerBI.
Machine Learning: Apply machine learning techniques to predict outcomes and increase business processes.

Requirements/Qualifications:

Education: Bachelor's or Master's degree in Computer Science, Information Systems, or related field.
Experience: 2+ years as a Data Engineer and/or Data Visualization & Analytics Expert.
Skills: Proficient in programming languages such as Python, Scala, Java, and C++ tailored for scalable data engineering solutions, expertise in data visualization tools (Power BI, Qlik, etc.), and experience with distributed data technologies like Spark and Hadoop.

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