Data Analyst

• Collaborate with business stakeholders to understand their data needs and requirements, and translate them into actionable insights and data-driven solutions.
• Perform data analysis tasks, including data cleaning, data transformation, and data visualization, to uncover meaningful patterns and trends in large datasets.
• Partner with data engineering to develop and maintain data pipelines and workflows, ensuring efficient and accurate data extraction, transformation, and loading (ETL) processes.
• Apply statistical analysis techniques and machine learning algorithms to identify correlations, predict outcomes, and optimize business processes.
• Assist in the development and maintenance of data models, data dictionaries, and data documentation to ensure data integrity and consistency.
• Conduct exploratory data analysis to discover insights and provide recommendations for improving business performance and decision-making.
• Collaborate with data engineers and data scientists to identify opportunities for automation and optimization of data processes and workflows.
• Monitor data quality and proactively identify and resolve data discrepancies or anomalies.
• Participate in cross-functional teams to support data-related projects, providing expertise and guidance on data analysis, data management, and data visualization.
• Work on business case development, project value proposition, and help with workload prioritization.

Experience:
•       Requires a minimum of 3 years of related experience.
•       Experience with Data visualization software like PowerBI, Tableau, and Looker.
•       Experience with Cloud Computing Platofrms such as GCP, Azure, and AWS.
•       Experience with Data Warehousing technology like Oracle Databases, SAP HANA, Google BigQuery
•       Proficiency in SQL for data querying and manipulation.
•       Proficiency in programming languages such as Python and R for data analysis and scripting.
•       Understanding of data modeling concepts and experience with data modeling tools.
•       Experience working with machine learning, statistical techniques and algorithms
•       Experience with ETL processes, data warehousing, and database management systems.
•       Excellent problem-solving and analytical skills, with attention to detail
•       Experience interacting with employees of all levels to present technical data in a non-technical manner.
•       Strong communication skills, with the ability to translate complex data concepts into understandable insights for non-technical stakeholders