Data Analyst

Job description

**Role & responsibilities** our future duties and responsibilities \\* Write advanced SQL and Python scripts to query, manipulate, and analyze complex datasets to identify actionable insights, trends, and anomalies. \\* Develop, maintain, and enhance dashboards and reports using BI tools (e.g., Power BI, Tableau) to provide clear and compelling visualizations of key business metrics. \\* Leverage your understanding of ETL processes to validate data as it moves through pipelines, troubleshoot data quality issues, and work with data engineering teams to ensure accuracy. \\* Partner with business stakeholders to understand their questions and challenges, and translate those needs into data-driven analysis and reports. \\* Identify opportunities to automate analytical processes and reporting, making data more accessible to the organization. Required qualifications to be successful in this role • Experience: 4+ years of experience in a Data Analyst, Business Intelligence Analyst, or similar role. • SQL Expertise: Expert-level proficiency in SQL, including window functions, complex joins, and performance tuning. You should be able to write queries to answer complex business questions from scratch. • Python for Analysis: Strong practical experience using Python for data analysis, particularly with libraries like Pandas, NumPy, and Matplotlib/Seaborn. • ETL Understanding: Solid conceptual understanding of ETL (Extract, Transform, Load) processes and data warehousing principles. You know how to trace data lineage and identify potential data quality pitfalls. • BI & Visualization: Hands-on experience creating dashboards and reports with at least one major BI tool (e.g., Power BI, Tableau, Qlik). Analytical Mindset: Exceptional analytical, critical thinking, and problem-solving skills with a high degree of accuracy. Good-to-Have Skills: • ETL Tool Exposure: Familiarity with viewing or debugging ETL jobs in tools like SSIS, Informatica, or Azure Data Factory. • Statistical Knowledge: Basic understanding of statistical analysis and modeling. • Cloud Environment: Experience working with data in a cloud environment (e.g., Azure Synapse, AWS Redshift, Google BigQuery). • Version Control: Familiarity with using Git for managing scripts. • Domain Knowledge: Previous experience in a specific business domain such as Finance, Marketing, or Operations is a strong plus **Preferred candidate profile**