Job Description

We are seeking an experienced and highly skilled Senior Data Analyst with a deep understanding of ETL processes , SQL , and Python to join our dynamic data team. The ideal candidate will have over 7 years of experience in data analysis, including working with large datasets, building ETL pipelines, and applying advanced SQL queries. You will be responsible for transforming raw data into actionable insights, automating data workflows, and supporting business decision-making through accurate and efficient data management. Key Responsibilities: Design, develop, and maintain ETL pipelines to extract, transform, and load data from various sources into structured data repositories. Write complex SQL queries for data extraction, data analysis, and reporting across multiple databases. Analyze and interpret data to provide actionable insights that drive business strategies and decisions. Develop and automate data workflows using Python for data processing, data cleaning, and analysis tasks. Collaborate with cross-functional teams, including product, engineering, and business teams, to understand data requirements and provide data-driven solutions. Build and manage data dashboards and reports for key stakeholders, ensuring the data is accurate, timely, and relevant. Troubleshoot, optimize, and improve ETL processes and data pipelines for better performance and scalability. Work with large datasets, ensuring data integrity, consistency, and quality. Ensure compliance with data governance and security protocols. Continuously evaluate and implement best practices for data analysis, reporting, and automation. Required Skills & Qualifications: Experience: 7+ years in data analysis, with a strong focus on ETL , SQL , and Python . ETL Expertise: Proven experience in building and maintaining ETL processes, using tools like Apache Airflow , Talend , Informatica , or other similar tools. SQL Proficiency: Advanced knowledge of SQL for complex queries, data manipulation, and performance tuning across various databases (eg, MySQL, PostgreSQL, SQL Server). Python Skills: Strong experience with Python for data manipulation, automation of tasks, and working with libraries such as pandas , numpy , SQLAlchemy , and matplotlib . Data Warehousing: Knowledge of data warehousing concepts, including data modeling and schema design. Data Visualization: Familiarity with data visualization tools such as Tableau , Power BI , or Looker to communicate insights effectively. Problem-Solving: Excellent analytical and problem-solving skills with the ability to think critically and propose data-driven solutions. Collaboration: Strong communication skills to effectively work with technical and non-technical teams. Education: A bachelors degree in Computer Science, Engineering, Mathematics, Statistics, or a related field. A masters degree is a plus.