Data Analyst

Experis to światowy lider rekrutacji specjalistów i kadry zarządzającej w kluczowych obszarach IT. Z nami znajdziesz konkurencyjne oferty zatrudnienia oraz ciekawe projekty IT skierowane zarówno do ekspertów z wieloletnim doświadczeniem, jak i osób, które dopiero zaczynają swoją przygodę w branży IT.

• 5+ years of experience in a data analyst or similar role, focusing on data visualization and analytics.
• Proven experience with Snowflake and Power BI for data management and visualization.
• Strong experience with SQL for querying and data manipulation.
• Hands-on experience with Python for data analysis and automation.
• Experience working with AWS cloud services (e.g., S3, Redshift, EC2) and understanding of cloud-based data solutions.
• Proficiency in ETL processes and tools, with a strong understanding of data integration best practices.
• Advanced Excel skills for data analysis and reporting.
• Knowledge of data modeling, data warehousing concepts, and relational databases.
• Familiarity with other BI tools (e.g., Tableau, QlikView) is a plus.

Data Analysis and Reporting:

• Analyze large and complex datasets to extract meaningful insights that support business decision-making.
• Develop, maintain, and enhance Power BI dashboards and reports to visualize data trends and patterns.
• Collaborate with business stakeholders to understand their data needs and deliver solutions that drive strategic initiatives.

Data Management and ETL:

• Design, implement, and manage ETL processes to efficiently ingest, transform, and store data in Snowflake.
• Ensure data accuracy, integrity, and security within the data warehouse.
• Optimize data pipelines for performance and scalability, incorporating best practices in data engineering.
• Write and optimize complex SQL queries to retrieve and manipulate data from various sources.
• Use Python for data analysis, automation, and to develop custom scripts for data processing.
• Implement data quality checks and validations to ensure the reliability of data outputs.

Cloud and Data Infrastructure:

• Utilize AWS cloud services to manage and store large datasets, ensuring efficient data access and processing.
• Work with cloud-based tools and services to support data analytics and business intelligence activities.
• Monitor and troubleshoot issues related to data infrastructure, ensuring smooth operations.