Analytics Engineer

Were seeking an Analytics Engineer to help design, build, and enhance our datadriven decisionmaking capabilities. The ideal candidate merges strong data handling, reporting, and analytical skills with an interest in statistical modelling and automation.

Key Responsibilities:

• Data Preparation & Quality: Collect, clean, and validate data from multiple internal and external sources to ensure accuracy, consistency, and completeness.
• Automation & Reporting: Build automated reports, recurring dashboards, and performancetracking tools for key business metrics.
• Exploratory Analysis: Perform exploratory data analysis (EDA) to identify trends, patterns, and actionable business insights.
• Business Collaboration: Partner with crossfunctional teams (product, operations, marketing) to translate business requirements into data solutions.
• Visualization & Storytelling: Support the development of interactive dashboards and data visualizations using BI tools (Power BI, Tableau, Looker, Google Data Studio).
• Technical Analytics: Generate regular and adhoc reports using Excel, SQL, Python, or similar tools to support decisionmaking.
• ML / Advanced Analytics Support: Assist in building, handling, and evaluating basic statistical or predictive models under guidance from senior analysts or data scientists.
• Continuous Improvement: Contribute ideas to improve data processes, pipelines, and reporting efficiency.

Required Skills & Qualifications:

• Bachelor's degree in mathematics, Statistics, Computer Science, Engineering, Economics, or a related field.
• Good understanding of statistics, probability, data structures, and fundamental data analysis concepts.
• Familiarity with Microsoft Excel, Google Sheets, or similar spreadsheet tools.
• Exposure to at least one programming language, preferably Python.
• Familiarity with SQL and databases is a plus.
• Basic understanding of machine learning concepts is an added advantage.
• Strong analytical, problem-solving, and communication skills.
• Eagerness to learn and grow in the field of data science and analytics.
• Attention to detail and ability to work effectively in a collaborative team environment.

What We Offer:

• Comprehensive training and mentorship from experienced data professionals.
• A collaborative, supportive, and learning-focused work environment.
• Opportunities to work on real-world business problems and practical data science use cases.
• Career growth opportunities in advanced analytics and machine learning roles.