.As an E-Commerce Data Analyst in the E-commerce Category & 4P Analytics Team, you'll tackle the most pressing and intriguing e-commerce challenges in category and supply chain domain, and will contribute to shaping HP's e-commerce future.
Our dynamic, highly skilled, and diverse global team is dedicated to data-driven problem-solving.
In this role, you'll combine your analytical prowess, technical skills, creativity and stakeholder engagement to innovate in HP' e-commerce strategies.
**About You**:- You are data-driven, with a passion for identifying patterns and insights, and driving these insights into action.- You excel at simplifying complex processes and making them more efficient.- You are solution-oriented: you see problems as puzzles and are relentless in solving them.- You are eager to learn and grow.
**Key Responsibilities**:- ** Analytics**: Conduct detailed data analysis to generate actionable insights that support decision-making across various business functions in e-commerce.
Conduct exploratory data analysis and deep dives to identify trends, anomalies, and opportunities for optimization across various domains, including marketing, operations, and finance.- ** Data Transformation & Cleaning**: Develop scripts and workflows using Python and SQL to clean, process, and transform large datasets from multiple sources into structured formats suitable for analysis.
Ensure adherence to data governance policies by validating data accuracy, consistency, and completeness across datasets and reports.- ** Data Visualization**: Create impactful, visually compelling dashboards and reports in Tableau, translating complex data into clear insights for non-technical stakeholders.- ** Collaboration with Engineering & Business Teams**: Work closely with data engineers, business analysts, and product teams to define data requirements and ensure alignment with business objectives.- ** Automation & Optimization**: Leverage Python scripting and SQL to automate routine reporting tasks and optimize data retrieval and analysis workflows, improving efficiency and reducing manual effort.
**Requirements**:- ** Technical Proficiency**:- ** SQL**: Advanced proficiency in writing complex queries, data manipulation, and optimization for large datasets.- ** Python**: Strong experience in data analysis libraries (e.G., pandas, NumPy), and automation of data processing tasks.- ** Git**: Familiarity with Git for version control and collaborative coding environments.- ** Tableau**: Expertise in creating interactive, dynamic, and visually appealing dashboards and reports.- ** Analytical Skills**: Strong analytical and problem-solving skills, with the ability to draw insights from complex data sets.- ** Business Acumen**: Ability to understand business processes and translate them into technical data requirements.- ** Attention to Detail**: Rigorous approach to data accuracy and integrity in reporting and analysis