Azure Cloud Data Analytics

JOB TITLE: Sr Cloud Data Analytics JOB LOCATION: Remote Eligibility: US Citizen or GC holder only REQUIRED EXPERIENCE: • SQL & Analytical Querying (non-negotiable / must-have) • Cloud analytics platforms expertise (Azure Synapse Analytics, Data Explorer, Power BI) • Experience with cloud platforms (AWS, Azure, GCP, Snowflake, etc.) • Python programming • Database management skills • Power Query & PowerApps • Strong analytical and problem-solving skills • Ability to interpret large and complex datasets Nice-to-have (secondary): • Apptio Platform (Cloudability, Apptio BI, TBM Studio) Sr Cloud Data Analytics Job Overview: Skilled data analyst focused on improving workflows and data insights based on data science and business intelligence. • A Cloud Data Analyst job description includes analyzing data stored in cloud platforms, using tools like SQL and Python to extract and interpret large datasets, and creating visualizations and reports for business stakeholders. • A cloud data analyst collects, processes, and analyzes large datasets stored in cloud-based platforms to provide actionable insights for business decisions. They use a range of tools and work with cross-functional teams to ensure data is accurate, secure, and accessible. While focusing on interpreting data, a cloud data analyst specializes in the unique aspects of cloud-based environments. This includes working with cloud-based data storage (such as Azure datasets, AWS S3 or Google Big Query), using cloud-native tools, and understanding cloud infrastructure for performance and cost optimization. • A cloud data analyst will collaborate closely with cross-functional teams to ensure the availability, reliability, and performance of our data systems and solutions. • A Cloud Data Analyst/Engineer designs, builds, and maintains data infrastructure and pipelines in a cloud environment to support business analytics. Key responsibilities include creating scalable data storage solutions, developing ETL/ELT processes, ensuring data security and compliance, and collaborating with other teams to meet data needs. Leverage cloud platforms like AWS, Azure, or Google Cloud to manage, process, and optimize large datasets for analysis. Skills: • SQL & Analytical Querying (Non‐Negotiable) a must • Expertise in cloud analytics platforms (Azure Synapse Analytics, Data explorer, Power BI) • Apptio Platform (Cloudability, Apptio BI and TBM Studio) a plus • Experience with cloud platforms such as AWS, Azure, GCP, Snowflake, etc. • Strong analytical, problem-solving skills and attention to detail. • Ability to interpret large datasets and complex information. • Strong knowledge of Python, database management, Power Query & PowerApps Roles and Responsibilities: • Partner with Data Engineer to build a FinOps Data Platform - design, implement, and optimize end-to-end data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data to produce a cloud cost chargeback dataset. • Data analysis to perform statistical analysis on datasets to identify trends, patterns, and anomalies. • Visualization and reporting, create comprehensive reports, dashboards, graphs, and other data visualizations to present findings in a clear and compelling ways for product team, finance and technology management. • Collaborate with Data Engineer, Dev Ops and Finance teams to translate business goals into data solutions, ensuring seamless data ingestion and transformation. • Work with cloud finance analyst on a monthly actuals analysis, forecasting session and annual budgeting process by integrating a Python script transforming big data into actionable facts. • Improved the efficiency of Excel working files used for monthly close analysis by integrating SQL and Power Query to finalize a journal entry submitted to accounting. • Creates and uses BI visualizations to identify meaningful insights from big data sources i.e. Azure, AWS, GCP, Snowflake, etc., interprets and communicates insights and findings from analysis associated to product, service, and business segments. • Design reports and analytic application, using Power BI (DAX) in a presentable and useful format that product team can leverage for clear insights and can also handle reconciliation analyses. • 6-8 years' experience • Process automation by setting up and maintaining automated data processes and pipelines to increase efficiency. • Implement data quality checks, monitor performance, ensure compliance with data governance and security policies, and manage access controls. • This enhancement allows the files to collect and organize data more quickly and provides a mechanism to detect specific accounting entries that deviated from the expected financial forecast. • Collaborate and work with data engineers, analysts, and other stakeholders to understand their data requirements and provide them with access to the data they need. • Collect, clean, and organize data from various cloud sources. • Analyze datasets to identify trends, patterns, and insights. • Develop and maintain dashboards, reports, and data visualizations. • Collaborate with data engineers, business teams, and IT professionals to understand data needs and objectives. • Perform data quality checks and assist in troubleshooting data-related issues. • Monitor data performance and suggest improvements. Key responsibilities involve collaborating with other teams, ensuring data quality, and translating business goals into data solutions to drive strategic decisions. The role requires proficiency with cloud services (e.g., AWS, Azure, Google Cloud) and strong analytical and problem-solving skills. The shift to the cloud allows analysts to handle larger datasets, access data from more diverse sources, and leverage technologies like AI and machine learning.