Data Analyst
Job Description & Overview
About Emoolar Technology Private Limited
Emoolar Technology Private Limited is a high-growth technology and innovation company operating in Work from home, India. Dedicated to delivering impactful digital solutions, the organization values agile execution, rapid product iteration, and continuous learning. Interns collaborate directly with seasoned technical leaders, contributing to meaningful projects that make a tangible impact across customer touchpoints and scalable systems.
About the Role
We are seeking a proactive and driven Data Analyst to join our Data Analyst team. This opportunity is structured as a Remote position based out of Work from home. In this role, you will apply theoretical knowledge to production challenges, collaborate with cross-functional colleagues, and help build reliable, performant solutions.
The selected candidate will receive structured guidance, participate in active sprint milestones, and gain end-to-end exposure to modern development lifecycles, team standups, and codebase management.
Key Responsibilities
- Extract, transform, and clean raw datasets from multiple operational sources and relational databases.
- Build high-impact interactive dashboards, KPI reports, and visual presentations using PowerBI and Tableau.
- Write optimized, modular SQL queries to uncover growth bottlenecks, user retention patterns, and operational efficiency.
- Partner with product and business stakeholders to translate strategic questions into actionable data insights.
- Perform cohort analysis, funnel tracking, and statistical hypothesis testing on product metrics.
- Maintain automated data hygiene checks and alert triggers for core metric anomalies.
Requirements & Qualifications
- Proficiency in SQL (joins, aggregations, window functions) and relational database concepts.
- Working experience with Python data science libraries (Pandas, NumPy, Matplotlib/Seaborn).
- Strong grasp of dashboard creation in business intelligence tools like PowerBI, Tableau, or Metabase.
- Curious analytical mindset with attention to detail and ability to synthesize data into clear recommendations.
- Pursuing or completed a Degree in Analytics, Statistics, Computer Science, Engineering, or a related discipline.
Stipend is paid upon completing assigned project milestones along with maintaining required attendance and task completion as evaluated by the host organisation.
Skills & Tech Stack
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Stipend, if applicable, is contingent on assignment to a paid project and completion of required certifications. Full terms apply.