Senior Cloud Data Analyst

At Pretius, we are looking for Senior Cloud Data Analyst to a project for global-scale platform in the field of gaming and lotteries.

• 7+ years of experience in data analytics, business intelligence, or data engineering-related roles.
• Strong proficiency in SQL and advanced analytical querying.
• Hands-on experience with cloud analytics platforms, including Azure Synapse Analytics, Azure Data Explorer, and Power BI.
• Experience with Apptio platform (Cloudability, Apptio BI, TBM Studio) is a plus.
• Proven experience working with cloud environments such as AWS, Azure, GCP, and Snowflake.
• Strong analytical and problem-solving skills with excellent attention to detail.
• Ability to interpret large, complex datasets and translate them into meaningful business insights.
• Advanced knowledge of Python for data analysis and data processing.
• Experience in database management and working with large-scale data systems.
• Familiarity with Power Query and PowerApps for data transformation, automation, and workflow optimization.

• Partner with Data Engineers to design, build, and optimize a FinOps Data Platform, including end-to-end data pipelines for ingesting, processing, and transforming structured and unstructured data for cloud cost chargeback datasets.
• Perform data analysis to identify trends, patterns, and anomalies, and deliver actionable insights for product, finance, and technology stakeholders.
• Develop reports, dashboards, and visualizations (e.g., Power BI, DAX) to support business, financial, and reconciliation analysis.
• Collaborate with Data Engineering, DevOps, Finance, and other stakeholders to translate business requirements into scalable data solutions.
• Support monthly actuals reporting, forecasting, and budgeting processes using Python-based automation and large-scale data processing.
• Improve reporting and financial close processes by leveraging SQL and Power Query, and automating Excel-based workflows.
• Build and maintain automated data pipelines to improve efficiency, scalability, and reliability of data processing.
• Ensure data quality through validation checks, monitoring, issue resolution, and performance optimization.
• Enforce data governance, security standards, compliance requirements, and access control policies.
• Collect, clean, and integrate data from multiple cloud platforms (Azure, AWS, GCP, Snowflake).